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FEMALE CHILDREN OF ALCOHOLICS: THEIR FUNCTIONING
IN EARLY AND MIDDLE CHILDHOOD

By

Leon I. Puttler

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Psychology

1996

ABSTRACT
FEMALE CHILDREN OF ALCOHOLICS: THEIR FUNCTIONING
IN EARLY AND MIDDLE CHILDHOOD
By

Leon I. Puttler

Children of alcoholics (COAs) have been found to be at greater risk for
developing alcohol problems, as well as other problems. As alcoholism is clearly a
heterogeneous disorder, there have been recent attempts to investigate the potentially
differing effects on male COAs as a function of parental alcoholism subtype. No
studies of young female COAs have yet examined this issue. This study examined
early cognitive and behavioral outcomes in a population-based sample of female
COAs, focusing on whether outcomes differed as a function of paternal alcoholism.

Participants were 126 girls (ages 3-11), and their parents, taking part in the
Michigan State University - University of Michigan Longitudinal Study. Child
outcome measures included the WISC-R, Stanford-Binet, WRAT-R, and Achenbach
Child Behavior Checklist (CBCL). Families were divided into Antisocial Alcoholics
(AALs), Nonantisocial Alcoholics (NAALs) and Controls based on whether fathers
met DSM-IV criteria for Alcohol Abuse/Dependence, and were high vs. low in
lifetime antisociality. Three-factor MANOVAS and ANOVAS (Risk Group X Age
Cohort X Parent Reporting) were used for the CBCL, while two-factor MANOVAS
and ANOVAS (Risk Group X Age Cohort) were used for other data.

Significant main effects for Risk Group were found for girls’ IQ, and for

CBCL Total Behavior Problems, Extemalizing Problems, and Social Problems. For
IQ and the CBCL Social Problem scale, girls in AAL families had lower functioning
than girls in Control families, with girls in NAAL families showing similar
functioning to Controls. For CBCL Total Problem Behaviors, and the Extemalizing
scale, girls in AAL and NAAL families had more problems than Controls; there was
no difference between girls from the two alcoholic groups.

The study also examined whether a cessation of alcohol problems in the
fathers was related to differences in daughters’ functioning. Girls in Non-Recovering
Alcoholic families had lower IQs, more Total Behavior Problems, more externalizing
behavior, and lower scores on the WRAT-R Spelling subtest than girls in Recovering
Alcoholic families. Daughters in Recovering Alcoholic homes were functioning at
similar levels to girls in Control families.

Results show that even at young ages, girls from alcoholic families have
lower levels of functioning than controls, and that there are some different familial .
and child effects based on the type of paternal alcoholism. Results also suggest that
the cessation of parental alcohol problems, and its concomitant change in family
environment factors, reduces the likelihood of decreased levels of functioning among

the girls raised in these homes.

ACKNOWLEDGMENTS

I am indebted to Robert Zucker for his willingness to take me on as his
student. He provided guidance, support, and theoretical vision which were
invaluable to me as I moved towards completion of this research.

I would also like to express appreciation to my other committee members,
Hiram Fitzgerald, Norman Abeles, and Ellen Strommen for their time, support, and
helpful suggestions. I would also like to thank Dr. Fitzgerald for helping me with
the various institutional procedures I needed to address in order to successfully
complete my degree. Dr. Abeles deserves a special thanks for his patience and
support towards me during my entire graduate school career, extended as it was.

I am further indebted to Susan Refior, Project Coordinator for the MSU-UM
Longitudinal Study, for her outstanding work with the families involved with the
project, as well as her professional and personal support over the last three years.
Ray Bingham deserves special recognition for assisting me with statistical and
computer consultation during this research. In addition, I would like to express
appreciation to the other Project staff for their various contributions to this research
project.

I am grateful to my parents for their personal and financial support throughout

my education. I am sorry that my father is not alive to see me successfully complete

iv

my degree; but his presence is felt.

Finally, I would like to express my utmost appreciation and thanks to the
many families participating in the MSU-UM Longitudinal Study. I have learned so
much from my interactions with them, and am constantly amazed at their willingness
to openly share information about themselves. Without their cooperation, none of
this work would be possible.

This research was supported by a grant to Drs. Zucker and Fitzgerald from

the National Institute of Alcohol Abuse and Alcoholism (R01 AA-07065).

TABLE OF CONTENTS

LIST OF TABLES ....................................................................... viii
CHAPTER 1
INTRODUCTION AND REVIEW OF THE LITERATURE ..................... 1
Children of Alcoholics .......................................................... 5
Cognitive Functioning ........................................................... 6
General Intellectual Functioning ............................................... 7
Academic Functioning .......................................................... 9
Behavioral Undercontrol ........................................................ 10
Other Emotional Functioning .................................................. 14
Health Problems .................................................................. 17
Concluding Remarks and Future Needs Regarding Children of
Alcoholics Literature ............................................................. 19
Typologies of Alcoholism ....................................................... 20
Alcoholic Subtypes and its Relevance to the Children of
Alcoholics Literature ............................................................. 26
CHAPTER 2
STATEMENT OF THE PROBLEM ................................................... 28
CHAPTER 2
HYPOTHESES ............................................................................ 30
CHAPTER 4
METHOD .................................................................................. 31
Participants ........................................................................ 31
Procedure ......................................................................... 34
Measures .......................................................................... 35
Parent Measures ......................................................... 35
Background Demographic Information ...................... 35
Parental Alcoholism ........................................... 35
Antisocial Behavior ............................................ 37
Alcoholic Subtype ............................................. 38
Child Measures .......................................................... 38
Female Target Child’s Current Behavior ................... 38
Intellectual Functioning ....................................... 40

vi

Academic Achievement ....................................... 41

Health Problems ................................................ 41

CHAPTER 5
RESULTS .................................................................................. 43
Missing and Problematic Data .................................................. 43
Demographic Variables ......................................................... 45
Child Outcome Variables ....................................................... 49
Intellectual Functioning ................................................ 49
Academic Functioning ................................................. 49
Child Behavior Problems .............................................. 49
Child Health Issues ..................................................... 56
The Effects of Recovery from Alcohol Problems .......................... 56
Child Outcome Variables .............................................. 57
Intellectual Functioning and Academic Achievement ..... 57
Child Behavior Problems ..................................... 60

CHAPTER 6
DISCUSSION ............................................................................. 64
Limitations of the Study ........................................................ 71
APPENDICES ............................................................................ 74
Appendix A: Drinking and Drug History Questionnaire ................. 74
Appendix B: Antisocial Behavior Inventory ............................... 87
Appendix C: Child Health and Developmental History .................. 80
LIST OF REFERENCES ............................................................... 104

vii

Table 1 -

Table 2 —

Table 3 -

Table 4 -

Table 5 —

Table 6 -

Table 7 -

Table 8 -

Table 9 -

Table 10 -

LIST OF TABLES

Number of Families with Girls in AAL, NAAL, and Control
Groups Across Ages 3-11 (N=126) ...................................... 46

Demographic Characteristics of AAL, NAAL, and Control Families
with Female Children ....................................................... 48

Z—Scores for Intellectual Performance of Girls in AAL, NAAL, and
Control Families Across Ages 3-11 ....................................... 50

Achievement Test (WRAT—R Standard Scores) Results of Girls in
AAL, NAAL, and Control Families Across Ages 6-11 .............. 51

Parents’ Ratings of Their Daughters’ Behavior Using CBCL Total
Behavior Problems and Broadband Factors in AAL, NAAL, and
Control Families Across Ages 3-11 (T-Scores) ........................ 53

Parents’ Ratings of Their Daughters’ Behavior Using CBCL
Narrowband Factors in AAL, NAAL, and Control Families Across
Ages 3-11 (T-Scores) ........................................................ 54

Demographic Characteristics of AAL and NAAL Families with Girls
Considering Fathers’ Recovery Status ................................... 58

Intellectual and Achievement Results of Girls in AAL and NAAL
Families in Recovering and Non-Recovering Homes .................. 59

Parents’ Ratings of Their Daughters’ Behavior Using CBCL Total
Behavior Problems and Broadband Factors in AAL and NAAL
Families with Fathers’ Recovery Status Considered (T-Scores) ..... 61

Parents’ Ratings of Their Daughters’ Behavior Using CBCL

Narrowband Factors in AAL and NAAL Families with Fathers’
Recovery Status Considered (T-Scores) .................................. 63

viii

Introduction and Literature Review

Although estimates of alcohol use disorders vary as a function of definition,
sampling strategies, and assessment techniques (Helzer, 1987), the 1992 National
Longitudinal Alcohol Epidemiologic Survey (Grant et al., 1994) estimated that 13.8
million individuals in the United States over age 18 met criteria for a DSM-IV
(American Psychiatric Association, 1994) diagnosis of Alcohol Abuse, Alcohol
Dependence, or both. As the use of alcohol has the potential to cause problems for
the individual drinker, for those persons coming into contact with the individual, and
for society in general, it is considered one of the major health problems in the United
States today (US. Dept. of Health and Human Services, 1993). Thus, there is great
interest in studying the etiology of alcoholism, identifying its risk factors and its
various manifestations.

Children of alcoholics (COAs) are a frequently used sample in these
endeavors as they are considered to be a high-risk population because, in part,
alcoholism tends to run in families (Cotton, 1979; Earls, 1987; Sher, 1991).
Although the genetic and environmental factors that contribute to risk for alcoholism
are not completely understood, progress in this endeavor is taking place (Sher,
1991). However, additional research using developmental system approaches is
necessary to better understand the trajectories leading to alcohol problems (Zucker,
Fitzgerald, & Moses, 1995). Such approaches have already been valuable for
understanding adolescent drug use (e. g. Brook, Whiteman, Gordon, & Cohen,
1986a, 1986b, 1989). Thus, similar kinds of work with young children at risk for

alcohol problems is currently in progress (e. g. Zucker, Noll, & Fitzgerald, 1986;

Zucker & Fitzgerald, 1992a).

COAs often show other problems in psychological functioning in addition to
their elevated risk for later alcoholism (El-Guebaly & Offord, 1977; Sher, 1991;
West & Prinz, 1987). Unfortunately, much of this research is overly simplistic in
that it fails to integrate the notion that there are different types of alcoholism (Ellis,
1992). Thus, there is little consideration about whether future risk for alcoholism, or
other behavior problems, varies with the alcoholic subtype of the parent(s) (i.e. with
some subtypes being at greater risk and others at less elevated risk). Although still
an empirical question, it is likely that subtyping COAs, based on the type of
alcoholism in their parents, would be more distinguishing than just identifying them
as a homogeneous class. Such efforts may also lead to a better understanding of the
many contradictory findings that exist in the COA literature to date. This work has
begun, with recent investigations showing distinctions between male COAs of
different parental alcoholism subtypes (e.g., Ellis, Bingham, Zucker, & Fitzgerald,
1996).

Another gap in the current COA literature is that, as with the adult alcoholic
literature, most of the focus is on males rather than females. This has been justified
by the observation that alcohol abuse/dependence is three times more common among
males than females (Grant et al., 1994). However, the fact that there are almost four
million alcoholic women in the United States suggests a problem worthy of
investigation. Studies focusing on female COAs are one means of addressing this
issue.

Previous COA studies that included females in their samples, often failed to

Zucker & Fitzgerald, 1992a).

COAs often show other problems in psychological functioning in addition to
their elevated risk for later alcoholism (El-Guebaly & Offord, 1977; Sher, 1991;
West & Prinz, 1987). Unfortunately, much of this research is overly simplistic in
that it fails to integrate the notion that there are different types of alcoholism (Ellis,
1992). Thus, there is little consideration about whether future risk for alcoholism, or
other behavior problems, varies with the alcoholic subtype of the parent(s) (i.e. with
some subtypes being at greater risk and others at less elevated risk). Although still
an empirical question, it is likely that subtyping COAs, based on the type of
alcoholism in their parents, would be more distinguishing than just identifying them
as a homogeneous class. Such efforts may also lead to a better understanding of the
many contradictory findings that exist in the COA literature to date. This work has
begun, with recent investigations showing distinctions between male COAs of
different parental alcoholism subtypes (e.g., Ellis, Bingham, Zucker, & Fitzgerald,
1996).

Another gap in the current COA literature is that, as with the adult alcoholic
literature, most of the focus is on males rather than females. This has been justified
by the observation that alcohol abuse/dependence is three times more common among
males than females (Grant et al., 1994). However, the fact that there are almost four
million alcoholic women in the United States suggests a problem worthy of
investigation. Studies focusing on female COAs are one means of addressing this
issue.

Previous COA studies that included females in their samples, often failed to

3

analyze the data for sex differences. Thus, the lack of differences between COAs
and controls, observed in some of these studies, may be due to true group differences
being masked by gender differences (Pihl, Peterson, & Finn, 1990). That is, males
and females may be differentially sensitive to the effects of living with an alcoholic
parent(s) (Searles & Windle, 1990). This may be even more true if parental
alcoholism subtypes are considered, as the potential different underlying
biopsychosocial processes may also differentially affect the offspring as a function of
the child’s gender.

According to Gomberg & N irenberg (1993), suggestions that the same
theoretical constructs can explain female and male alcoholism are not supported by
recent studies. For example, Gomberg and N irenberg reviewed studies showing that
there is a higher comorbidity of other psychological disorders in female alcoholics
than male alcoholics. In addition, the authors suggested that the consequences of
alcohol-related problems may be more severe for women than men, in terms of the
woman’s psychological functioning, interpersonal functioning, health-related issues,
and social attitudes about her drinking.

Wilsnack and Wilsnack (1993) identified several psychosocial risk factors for
problem drinking in women, including depression, sexual dysfunction, a lack of
stable social roles, low self-esteem, and a history of childhood sexual abuse. The
pathways leading to alcoholism in women more than likely include genetic
vulnerabilities as well (Hill, 1993). Hill reviewed the extant literature and derived
evidence to support the hypothesis that there are at least two types of alcoholism in

women. One of these types results from environmental pressures, growing out of

4

late-onset heavy drinking (peak ages are 35-49). A second type has an earlier onset
(between 18-24) and appears to be more genetically mediated.

Additional discussion regarding possible female subtypes of alcoholism will
take place in a later section of this literature review. However, it is clear that
alcoholism in women is also heterogeneous, and perhaps derives from developmental
pathways that result in at least two types. Thus, there is clearly a need to investigate
early development of alcoholism in females. The goal of the present investigation
was to complete gaps in the current literature by examining the early origins of
problems in young female children of alcoholic fathers, who are further differentiated
by comorbid symptomatology. The study characterizes early origins of problems for
these female COAs both in terms of potential risk factors for later alcoholism, as
well as for other problematic outcomes.

This review, then, turns first to a more thorough discussion of the literature
regarding COAs. The emphasis here is on cognitive, behavioral, emotional, and
health factors; other factors such as biochemical markers are beyond the major focus
of the current work (see Sher, 1991, and Windle & Searles, 1990, for reviews of the
biological literature). Knowledge already obtained about female COAs is
highlighted. Throughout the review, potential gender differences are also noted.

A brief review of the literature on alcoholic subtypes follows. Finally,
possible linkages between the COA and alcohol subtyping literatures are discussed,

providing the basis for the current investigation.

5
Children of Alcoholics

Methodological inadequacies limit the interpretation of many of the findings
from COA research, making it difficult to draw firm conclusions about the effects of
growing up in an alcoholic environment (Seilhamer & Jacob, 1990; Sher, 1991; West
& Prinz, 1987). Some of these shortcomings involve sampling issues, while others
are more related to assessment and analysis. Some sampling problems in prior
studies include: (a) lack of adequate control groups (e.g. Herjanic, Herjanic, Wetzel,
& Tomelleri, 1978; Tarter, Hegedus, Goldstein, Shelly, & Alterman, 1984); (b) wide
age ranges in samples of COAs without analyzing possible differences among these
various ages (e.g. Ervin, Little, Streissguth, & Beck, 1984; Herjanic et al., 1978);
(c) use of clinic samples of alcoholic parents, thus limiting the generalizability of
findings (e. g. Moos & Billings, 1982; Murphy, O’Farrell, Floyd, & Connors, 1991);
and, as already mentioned above, (d) a lack of information about female COAs.

Other methodological issues include: (a) inconsistent or vague criteria for
diagnosing alcoholism in the parents (e. g. Churchill, Broida, & Nicholson, 1990;
Marcus, 1986); (b) little attention to drinking-related variables such as duration and
severity of parental alcoholism (e. g. Marcus, 1986; Saunders & Schuckit, 1981); (c)
failure to examine multiple sources of information (e. g. Aronson & Gilbert, 1963;
Saunders & Schuckit, 1981); and ((1) failure to address possible confounding
variables such as SES, other psychopathology in the parents, and other family
variables such as disorganization (e. g. Fine, Yudin, Holmes, & Heinemann, 1976;
Prewett, Spence, & Chaknis, 1981). However, perhaps the greatest weakness in the

COA literature is the failure to significantly address the heterogeneity involved,

6

despite all indications that there is more than one type of alcoholism.

Despite these methodological limitations, and the often contradictory findings
in previous studies, reviewers of the literature on COAs (El-Guebaly & Offord,
1977; Sher, 1991; West & Prinz, 1987) have concluded that as a whole, there is an
association between parental alcoholism and an increased incidence of deficits and
behavior problems in children from these families (both when they are children and
when they become adults). General conclusions suggest that COAs, in comparison to
non-COAS, are more likely to be hyperactive, to engage in antisocial behavior, to
have lower academic achievement, to have lower cognitive abilities, to have more
negative alcohol consequences, and to have greater expectancies for positive
reinforcement from alcohol (Sher, 1991). However, whether these conclusions hold
for female COAs, as well as male COAs, is less well understood. Also, many
children, in fact a majority of those children from alcoholic homes, do not develop
psychological disorders (West & Prinz, 1987). Thus, there is a need to continue
studying individual differences in COAs in order to uncover specific factors leading
to various outcomes (West & Prinz, 1987).

Cognitive Functioning

Drawing conclusions about the effects of parental alcoholism on children’s
cognitive functioning is difficult due to the different types of measures used to assess
intellectual and academic functioning, the number and nature of comparison groups,
control for prenatal exposure to alcohol, and identification of additional stressors that
may adversely affect children’s development and performance (West & Prinz, 1987).

Nevertheless, there appears to be substantial evidence that COAs have cognitive and

academic deficits relative to non-COAs.

General Intellectual Functioning. With regards to IQ, several studies have
found significantly lower IQs in COAs as children and as adults (Aronson,
Kyllerrnan, Sabel, Sandin, & Olegard, 1985; Bennett, Wolin, & Reiss, 1988; Drejer,
Theilgaard, Teasdale, Schulsinger, & Goodwin, 1985; Ervin et al., 1984; Gabrielli &
Mednick, 1983; Steinhausen, Nestler, & Huth, 1982; Streissguth, 1976; Streissguth,
Little, Herman, & Woodell, 1979). Other studies do not report lower IQs in COAs
(Fitzgerald et al., 1993; Herjanic et al., 1978; Johnson & Rolf, 1988; Tarter et al.,
1984), although many of these show a nonsignificant trend in this direction. It
should also be pointed out that those studies that showed significant differences often
found that the COAs still fell within normal ranges (Sher, 1991). Thus, the IQ
differences observed between COAs and non-COAs appear to be relative, rather than
actual deficits.

One explanation for the contradictory findings regarding IQ is that most of the
differences in these studies appear related to areas of verbal ability and
abstracting/conceptual reasoning abilities (Hesselbrock, Bauer, Hesselbrock, &
Gillen, 1991). Studies using measures that do not more finely differentiate IQ may
be attenuating possible true differences. Another confounding factor in many of
these studies (both those with positive and negative findings) is the failure to control
for prenatal exposure to alcohol, and thus its potential impact on the COA’s current
functioning.

Confounding factors are also demonstrated in the results of another study

(Noll, Zucker, Fitzgerald, & Curtis, 1992). This research found lower

8

Developmental Quotients in very young male COAs. However, such differences
existed only in the area of personal/ social development when other factors such as
SES and stimulation of home environment were controlled. These results point to
the importance of controlling factors that may contribute to cognitive deficits other
than parental alcoholism.

Finally, another study looking at intelligence in COAs (Kern et al., 1981)
reported potential gender differences. In this investigation, results showed lower IQs
in male children of alcoholics, but not when male and female COAs were combined.
The other studies cited above did not analyze possible gender differences when
mixed-gender samples were used.

Other research has looked at more specific cognitive-perceptual attributes and
neuropsychological functioning. Again, there are conflicting results (see reviews by
Pihl et a1. , 1990; Windle, 1990, for additional details). One noteworthy finding
among these studies is evidence that COAs may have decreased planning ability,
impulse control, and impaired problem-solving abilities (Tarter, Jacob, & Bremer,
1989; Wilson & Nagoshi, 1988). Such deficits may be important to the findings of
increased hyperactivity/attention problems often observed in COAs. In addition,
almost all the significant differences between COAs and non-COAs reported in
Wilson and Nagoshi’s study (1988), were in the form of three-way interactions with
gender and age. This again suggests the importance of not assuming similar effects
among male and female COAs, but rather investigating potential differences between

the sexes.

9
Academic Functioning. Researchers have looked at academic differences

between COAs and non-COAs, again with conflicting results. Studies using
standardized measures of academic functioning have generally found that COAs show
impaired functioning relative to non-COAs (Bennett et al., 1988; Ervin et al., 1984;
Hegedus, Alterman, & Tarter, 1984; Marcus, 1986). However, Johnson and Rolf
(1988) reported no reduced academic functioning in COAs using the Wide Range
Achievement Test - Revised (WRAT-R; Jastak & Wilkinson, 1984), although
maternal ratings of the children from the School Competence score of the Child
Behavior Checklist (Achenbach & Edelbrock, 1983) and the Cognitive Competence
subscale of the Perceived Competence Scale for Children - Parent Version (Harter,
1982) showed lower cognitive competencies and expectations.

Other aspects of school performance, frequently using school records, were
also studied with COAs showing lower grade point averages and more repeating of
grades (Schuckit & Chiles, 1978), generally poorer schoolwork (Hughes, 1977), a
decreased likelihood to graduate from high school despite no differences in IQ or
cognitive skills (Miller & Jang, 1977), and a greater number of repeated grades and
referrals to school psychologists (Knop, Teasdale, Schulsinger, & Goodwin, 1985).
Nevertheless, there is contradictory evidence as other investigators have not found
significant academic deficiencies in COAs (Murphy et al., 1991; Rirnmer, 1982).
Interestingly, a gender difference was found in one of these studies (Murphy et al.,
1991) showing that daughters of alcoholics had more variability in school attendance

than did sons of alcoholics.

10

Bali/i031] Undercontrol

Behavioral undercontrol is an umbrella term for several constructs such as
antisocial behavior, aggression, rebelliousness, impulsivity, inattention, hyperactivity,
and delinquency (Windle, 1990). A number of longitudinal studies have shown a
relationship between behavioral undercontrol as a child and subsequent adult alcohol
abuse (Jones, 1968; Loper, Kammeier, & Hoffman, 1973; McCord & McCord,
1960; Robins, 1986; Vaillant, 1983). This relationship is descriptive of women, as
well as men (e. g. Robins, 1986).

Some studies have investigated behavioral undercontrol in COAs through the
use of personality scales such as the MacAndrew Alcoholism Scale (MAC;
MacAndrew, 1965), a Minnesota Multiphasic Personality Inventory (MMPI) -
derived scale that samples undercontrolled traits. Evidence exists that young,
nonalcoholic, adult COAs score higher than controls on the MAC (Knowles &
Schroeder, 1989; Saunders & Shuckit, 1981). Mann, Chassin, and Sher (1987)
reported a similar finding with COAs in a high-school sample using items from the
MAC, and items from the California Personality Inventory socialization scale. Sher,
Walitzer, Wood, and Brent (1991) also demonstrated differences between college
freshmen COAs and non-COAs on similar measures of behavioral undercontrol. In
this study, men showed more behavioral undercontrol than women, although no
significant Gender X Family History interactions were observed.

Sher (1991) pointed out that many of the statistically significant differences
between COAs and non-COAs on these personality measures have rather small effect

sizes, and therefore are of questionable clinical significance. Other studies, have

11

failed to show differences in behavioral undercontrol using similar personality
measures with college-aged or older COAs and their peers (Alterman, Bridges &
Tarter, 1986; Alterman, Searles, & Hall, 1989; McKenna, & Pickens, 1983).
Although these personality measures show contradictory findings, there is
other evidence suggesting that COAs display more behavioral undercontrol than their
peers. Using the Child Behavior Checklist (Achenbach & Edelbrock, 1983), a
parental rating of children’s behavior, studies have shown that male and female
COAs tend to score higher on the Extemalizing scale (measuring behavioral
undercontrol) than non-COAs (Chassin, Rogosch, & Barrera, 1991; Jacob &
Leonard, 1986; Rubio-Stipec, Bird, Canino, Bravo, & Alegria, 1991). Other studies
have found an association between parental alcoholism and childhood conduct
problems (Fine et al., 1976; Merikangas, Weissman, Prusoff, Pauls, & Leckman,
1985; Steinhausen, Gobel, & Nestler, 1984; Steinhausen, Nestler, & Huth, 1982;
Stewart, deBlois, & Cummings, 1980; Stewart, deBlois, & Singer, 1979). Studies
have also supported an association between parental alcoholism and delinquent and/or
truant outcomes for the children in these families (Alterman, Bridges, & Tarter,
1986; Chafetz, Blane, & Hill, 1971; Fine et al, 1976; Hughes, 1977; Miller & Jang,
1977; Offord, Allen & Abrams, 1978: Rimmer, 1982; Robins, West, Ratcliff, &
Herjanic, 1978; Schuckit & Chiles, 1978; Werner, 1986). Finally, a relationship
exists between parental alcoholism and substance abuse (alcohol or other substances)
in adolescents (Chasin et al., 1991; Herjanic, Herjanic, Penick, Tomelleri, &
Armbruster, 1977; Lund & Landesman-Dwyer, 1979; Merikangas et al., 1985;

Rydelius, 1983; Schuckit & Chiles, 1978).

12

The linkage between childhood hyperactivity and parental alcoholism is
another area that sheds light on the issue of behavioral undercontrol. Early studies
found an increased prevalence of alcoholic parents in families of hyperactive children
(Cantwell, 1972; Morrison & Stewart, 1971). More recent studies evaluating
children of alcoholic parents have also found relationships between parental
alcoholism and child hyperactivity (Aronson & Gilbert, 1963; Aronson, Kyllerman,
Sabel, Sandin, & Olegard, 1985; Bell & Cohen, 1981; Fine et al., 1976; Knopp et
al., 1985; Lund & Lundesman-Dwyer, 1979; Schulsinger, Knop, Goodwin,
Teasdale, & Mikkelsen, 1986; Steinhausen et al., 1982). Such a relationship was
even reported in very young children with respect to parents’ ratings of their child’s
hyperactivity (Ham, Fitzgerald, & Zucker, 1993), and young children’s observed
level of irnpulsiveness (Fitzgerald et al., 1993).

Contradictory evidence is not easily found in this area. One study did report
COAs as less impulsive than non-COAs (Tarter, Hegedus, Goldstein, Shelly, &
Alterman, 1984). However, all subjects in this study were from a delinquent
population; not the most appropriate sample due to high overall levels of impulsive
behavior among both groups. This last study, though, points out one problem in the
linkage between parental alcoholism and hyperactivity. That is, a controversy exists
as to the comorbidity of hyperactivity and conduct disorder (Hinshaw, 1987).
Hinshaw suggested that there is overlap between hyperactivity and conduct disorder,
although subgroups of children within these domains differ. Over the years, a
greater distinction has been made in diagnostic practices between

attention/hyperactivity behavior and impulsive/delinquent behavior, with separate

13

disorders currently identified in DSM-IV (American Psychiatric Association, 1994).
However, many of the studies reported above do not clearly delineate these
differences. Thus, it remains inconclusive as to whether it is hyperactivity (in an
activity sense), attention problems, impulsivity, aggression, or various combinations
of these factors which may be the greater differentiating factor between COAs and
non-COAs.

In conclusion, although there are currently some contradictory findings
making solid conclusions difficult to draw, there is evidence that COAs tend to be
characterized by an undercontrolled behavioral style (Sher, 1991; Windle, 1990).
Much less clear though is whether this is true for female COAs as well as male
COAs. In fact, the entire literature on externalizing behavior among girls in the
general population is quite sparse (Lahey & Loeber, 1994). However, Lahey and
Loeber suggested that there are key differences among genders, as girls with conduct
disorders tend to have later onset and less aggressive behavior than boys with similar
problems. This again points to the need to take a more developmental perspective
when studying the etiology of behavioral disorders.

Most of the COA studies reviewed above did not analyze potential gender
differences when females were included in the samples. The few that did do not
currently provide sufficient data to form conclusions. For example, Chafetz et al.
(1971) showed no significant differences between genders in terms of externalizing
behavior despite some overall differences between COAs and non—COAs. Sher et al.
(1991) found greater family alcoholic effects for women, than men, in their study of

college-aged COAs, but none specifically related to externalizing behavior. Jacob

14

and Leonard (1986) found significant differences in problem behavior among boys of
alcoholic and boys of depressed parents (versus controls), but similar problem
behavior only in girls of the depressed parents (i.e. no differences between girls of
alcoholic parents and controls). Thus, this study provides evidence that parental
alcohol may not impact girls as much as boys in terms of problem behavior. On the
other hand, Chassin et al. (1991) found greater externalizing problems in children of
alcoholic parents with no overall gender differences. However, the girls in their
sample with an alcoholic mother and nonalcoholic father showed the most
externalizing behavior, while boys with two alcoholic parents showed the most
externalizing behavior. This study suggests that there are potential gender
differences in externalizing behavior based on which, or how many, parents of the
child has the alcohol difficulties. Clearly then, additional research with female
COAs is needed to understand more fully if behavioral undercontrol issues are a
distinguishing factor for them, as they seem to be for their male counterparts.
Other Emotional Functioning

There is considerable comorbidity between alcoholism and more internalized
disorders such as depression and anxiety, especially in females (Sher, 1991). Thus,
research has looked at the levels of these disorders in COAs with at least some
support for increased problems in COAs (Russell, Henderson, & Blume, 1985).
However, a review of the literature leads to difficulties in determining which
emotional issues or problems account for the observed differences between COAs
and non-COAs. For example, West and Prinz (1987) reviewed ten investigations

showing a positive association between parental alcoholism and impaired emotional

15

functioning. However, the dependent variables in the reviewed studies covered
various aspects of emotional functioning including depression, anxiety, lowered self-
esteem, and perceived lack of control over one’s environment. In addition, West and
Prinz suggested that this body of research is plagued by methodological problems,
similar to those already discussed, such as nonstandardized assessment measures,
uncorroborated self-report measures, and designs for which effects cannot be
attributed directly to parental alcoholism. Nevertheless, a more extensive review of
these findings is necessary since these types of internalizing problems may be most
pertinent to studies focusing on female COAs.

Studies have shown increased depression or lowered mood states in COAs
(Hughes, 1977; Moos & Billings, 1982; Rolf, Johnson, Israel, Baldwin, & Chandra,
1988; Schuckit & Chiles, 1978), as well as elevations on various rating or
personality scales measuring depressive symptoms (Anderson & Quast, 1983; Tarter
et al., 1984). Studies using the Achenbach CBCL (measuring other aspects of
internalizing behavior in addition to depression) also found COAs generally showing
greater problems (Chassin et al., 1991; Jacob & Leonard, 1986; Rubio-Stipec et al.,
1991). However, the results of one of these studies found inconsistent reports
between the parents and the adolescents in the sample; the parents reported greater
problems for COA adolescents, while the COAs did not rate themselves as different
than their non-COA peers (Chassin et al., 1991).

Studies looking at a broader definition of emotional problems (psychiatric or
emotional distress) have also reported that COAs have more problems than non-

COAs (Sher et al., 1991; Steinhausen et al., 1984). Included in these definitions are

16

anxiety disorders as well as depression.

Besides actual anxiety disorders, some studies have looked at the possibility of
heightened arousal, or heightened emotionality, as being a personality trait in COAs.
The results of these studies (Finn & Pihl, 1987; Knop et al., 1985; Schuckit, 1982)
showed no significant differences between COAs and non—COAs (males were the
only subjects in two of the studies and the majority of subjects in the third sample
also were male), although one study (Finn & Pihl, 1988), using a sample of males
only, found some mixed results. This last study looked at differences among
multigenerational (parents and grandparents) COAs and unigenerational (parents only)
COAs. Multigenerational COAs, but not unigenerational COAs, were more
problematic on a neurotic scale than non—COAs. On the other hand, unigenerational
COAs, but not multigenerational COAs, rated themselves as higher on emotionality
than non-COAs. Thus, overall, evidence supporting heightened arousal or
emotionality in COAs is not very strong (Sher, 1991; Windle, 1990).

A couple of studies explored the impact of parental alcoholism on children’s
locus of control. These studies (Kern et al., 1981; Prewett et al., 1981) found
younger COAs to have a more external locus of control than their non-COA
counterparts. However, there is also evidence that such differences diminish with
age as adolescent and adult COAs do not show greater external locus of control
relative to their same-aged peers (Churchill et al., 1990; Russell et al., 1985).

Finally, there is some evidence that COAs tend to have lower self-esteem than
non-COAs (Bennett et al., 1988; Berkowitz & Perkins, 1988; Hughes, 1977; Sher et

al., 1991; Roosa, Sandler, Beals, & Short, 1988). However, other studies have not

17

replicated these findings (Churchill et al., 1990; Herjanic et al., 1977; Herjanic et
al., 1978). Again, though, methodological differences among the studies appear to
be the major reason for these contradictory findings (e. g. the use of different, and
some less rigorous, assessment measures, and the use of quite different samples in
these studies). In addition, it is not clear if lowered self-esteem reflects a personality
dimension or a response to feelings of depression (Sher, 1991).

In conclusion, there is some evidence that COAs may be at risk for
developing a variety of anxiety-depressive symptoms. However, inconsistencies
among studies cloud the picture. Although it is not the only improvement that might
assist in teasing out the true nature of these type of problems with COAs, studies
paying more attention to possible gender differences, as well as to different alcoholic
subtypes, could be of great assistance.

Health Problems

Although not as extensively researched, the issue of child physical health
problems, other than those created by Fetal Alcohol Syndrome, has also been of
interest in studies of COAs. This also is the area where the most gender differences
have been reported.

Biek (1981) found that somatic complaints were reported almost twice as often
in medical clinic outpatients with a problem-drinking parent as in those without a
problem-drinking parent. Of the group reporting a problem-drinking parent, 78% of
them were female.

Steinhausen et al. (1982) conducted structured interviews regarding the

frequencies of various symptoms in children born to epileptic, alcoholic, or healthy

18

mothers. Results indicated that children of alcoholic mothers were significantly more
impaired than the other two groups in rates of outpatient therapy, eating problems,
headaches, and sleeping problems.

Roberts and Brent (1982) found that female members of alcoholic families had
higher physician utilization rates and higher numbers of distinct diagnoses than did
their matched controls. A similar result was not found for males on these two
indices. Unfortunately, both spouses and children of an alcoholic were included in
these analyses, making it difficult to conclude whether it was the adult, the COA, or
both, who contributed to the observed difference. Nevertheless, this study suggests
significant gender differences.

On the other hand, two studies have not found significant differences in
physical health problems among COAs (Moos & Billings, 1982; Rimmer, 1982).
Rimmer found no differences in the rates of health problems among children of
parents hospitalized for alcoholism, depression, or obstetrical-gynecological
problems. However, West and Prinz (1987) suggested that one reason for these
negative results may have been the more stringent definition of health problems used
by Rimmer.

Finally, Moos and Billings (1982) compared the health status of children in
families of recovered alcoholics, relapsed alcoholics, and non-alcoholics. When
physical problems were considered individually, no differences among the groups
were found. However, on a composite measure of physical problems, children of
relapsed alcoholics showed a tendency (though not statistically significant) to have

more problems than control children.

19
Concluding Remarks and Future Needs Regarding the COA LiteLature

 

As can be seen from the review above, although much data has been gathered
about the effects of growing up with parental alcoholism, conclusions are still
difficult to draw. As discussed at the outset of this review, methodological
limitations of several of the studies are responsible for many of the current problems.

Although not all these issues can be addressed in a single study, there are
several areas which investigations have especially ignored that could provide needed
information towards better understanding of COAs. First, a greater understanding of
the effects of parental alcoholism on female COAs is needed, given that there are
indications of different sensitivity to growing up in an alcoholic environment based
on one’s gender. Second, the majority of the COA literature has focused on older
COAs (older children, adolescents, or adults), virtually ignoring potential effects on
the development of very young COAs. Yet, a few studies with very young male
COAs showed that effects are already distinguishable at these young ages. Similar
studies with very young females are thus needed to see if similar results are found.

Third, most of the studies reviewed involved clinical alcoholic families (i.e.
those recruited based on the fact that they were involved in some form of treatment).
This limits the generalizability of these findings. Studies using community-based
samples are needed to corroborate some of the results from these more restricted
studies.

Fourth, some results suggest the need to address potential moderating effects
when, and if, parental alcohol problems curtail during the child’s development.

There is evidence that the family functioning in homes of recovered alcoholics

20

appears more like that of nonalcoholic families, than like current alcoholic families
(Moos & Billings, 1982). One would therefore expect that such factors would
decrease the risk for the development of problems in the children from these
recovered alcoholic homes. However, an important area requiring future
investigation is whether there is a certain critical period in the child’s development
during which the recovery status of the parent moderates future risk.

Finally, although some studies have addressed co—existing factors in addition
to parental alcoholism, the issue of the heterogeneity of alcoholism itself (e. g.
different subtypes) has been virtually ignored. It is to this issue that I turn next.

Typologies of Alcoholism

Since the late nineteenth century, clinicians and researchers have attempted to
identify subtypes of alcoholics (Babor & Lauerman, 1986). Babor and Lauerrnan
noted that these classification schemes were often based upon the alcoholic’s drinking
pattern, the chronicity of alcoholic symptoms, various etiological theories, and other
behavioral and psychophysiological variables. Most past attempts at classification
have not gained wide acceptance because they have failed to meet some of the
criteria necessary for a useful system such as homogeneity within categories,
heterogeneity between categories, stability, comprehensiveness and specificity,
multidirnensionality, utility, and validity (Babor & Meyer, 1986). However, in
recent years, new attempts to develop valid typologies have occurred due to the
increased awareness of the heterogeneity of alcoholics, and the need to understand
alternate etiological pathways which may lead to more effective prevention and

treatment (Zucker, 1994).

21
Jellinek (1960) classified alcoholics (he did not specify whether he was

addressing males, females, or both) into five types based on different progressive
stages: alpha, beta, gamma, delta, and epsilon. Jellinek suggested that alpha and
beta alcoholics experience psychological dependence, but not loss of control over
their drinking. Beta alcoholics differ from alpha ones in that they may exhibit
medical problems, although neither are physically dependent on alcohol. Gamma
alcoholics do show signs of physical addiction, as well as loss of control over their
drinking. Jellinek described gamma alcoholism as the species that produces the most
serious kinds of damage to the individual (medically, psychologically, and socially).
However, gamma alcoholics are able to abstain from drinking without serious
withdrawal symptoms. Delta alcoholics experience withdrawal symptoms when
abstaining from drinking, as well as being psychologically and physically dependent
on alcohol. They can control the amount of their intake, although some use is
needed to reduce the withdrawal symptoms. Finally, Jellinek termed epsilon
alcoholics as periodic drinkers. He did not further define, or describe, this type of
alcoholism as he believed it was the least known species.

Hesselbrock (1986) pointed out that Jellinek’s typological system is similar to
that used in DSM-III (American Psychiatric Association, 1980). Alpha and beta
alcoholics are similar to DSM-III criteria for alcohol abuse, while gamma and delta
alcoholics conform to criteria for alcohol dependence. DSM-III-R (American
Psychiatric Association, 1987) and DSM-IV (American Psychiatric Association,
1994) criteria continue to show this distinction between addicted and non-addicted

alcoholics. A weakness, though, in Jellinek’s classification schema is the fact that it

22

does not adequately deal with the diversity and multidimensional nature of
alcoholism; that is, the individual variability of those alcoholics who do not follow
the prescribed sequence of stages (Hesselbrock, 1986).

Classification systems which have received the most attention recently have
grown out of etiological theories of alcoholism (Ellis, 1992). Cloninger and his
colleagues (Cloninger, Bohman & Sigvardsson, 1981) developed a typology based
upon genetic research consisting of two types of alcoholism. Type I, or milieu—
lirnited, alcoholism is characterized by a late adult onset, little criminality, and is
associated with loss of control, and guilt over drinking. It may be inherited through
both male and female relatives, although it is also seen as more environmentally than
genetically mediated. Type II, or male-limited alcoholism, has an earlier onset, is
often associated with aggressive, impulsive behavior, and is more heavily genetically
rather than environmentally mediated. As implied by the name, it occurs almost
exclusively in males. Although Cloninger and his colleagues have found research
evidence supporting this classification system, a limitation to their subtypes is a
failure to distinguish developmental antecedents, particularly environmental ones, for
each type of alcoholism (Zucker, Ellis, & Fitzgerald, 1994a). In addition, a
substantial number of alcoholics cannot be equivocally classified as Type I or Type II
(Zucker et al., 1994a).

Using cluster analyses of 17 defining characteristics including premorbid risk
and vulnerability, severity of dependence and alcohol-related factors, chronicity and
negative alcohol-related consequences, and comorbid psychopathology, Babor and his

colleagues (Babor et al., 1992) proposed another multidimensional typology. Two

23

types of alcoholics were identified which are somewhat similar to Cloninger’s
subtypes. Type A alcoholics were characterized by less premorbid risk and
vulnerability, later onset, less severe dependence, fewer alcohol—related problems, a
less chronic course with fewer negative consequences of alcohol consumption, and
less comorbid psychopathology. Type B alcoholics were characterized as having
more premorbid risk and vulnerability, earlier onset, more severe dependence and
alcohol-related problems, a more chronic course with more negative consequences of
alcohol consumption, and more comorbid psychopathology. Subsequent studies
(Brown, Babor, Litt, & Kranzler, 1994; Litt, Babor, Del Boca, Kadden, & Cooney,
1992) have shown this typology to have clinical utility for treatment matching in
male alcoholics. However, at present, its validity for female alcoholics remains
unclear.

Zucker (1987, 1994) proposed at least four different subtypes of alcoholism,
each with its own cause and course. Antisocial Alcoholism is hypothesized to have a
genetic diathesis, an early onset of both alcohol-related and antisocial behavior, and a
significant background for family history positive for alcoholism. In addition, there
is evidence suggesting that high levels of other drug involvement are also found
among antisocial alcoholics (Zucker, 1994). The existence of Antisocial Alcoholism
has already been identified in several different adult populations (e.g. Babor et al.,
1992; Zucker et al., 1994b; Zucker, Ellis, Fitzgerald, Bingham, & Sanford, in
press).

Developmentally Limited Alcoholism is characterized by frequent, heavy

drinking which peaks during the early 20’s, then remits to more social drinking with

24

the successful assumption of adult career and family roles. What distinguishes this
subtype from Antisocial Alcoholism is that it is life-stage specific, and a normative
process of adolescence for a large subset of individuals (Zucker, 1994).

Negative Affect Alcoholism is the third proposed alcoholism subtype. This
type of alcoholism is more common in women, and often involves the use of alcohol
for mood regulation or enhancement of social relationships. Zucker (1994) noted
that adult longitudinal data bases generally provide support to a negative affectivity
syndrome leading to later problematic alcohol involvement. However, he added that
additional longitudinal work with children is necessary to establish a true causative
pathway from depression to alcoholism.

Originally, Zucker (1987) suggested Developmentally Cumulative Alcoholism
as the fourth subtype. Any genetic diathesis that was posited to exist in this form of
alcoholism was hypothesized to be environmentally mediated. Thus, in this subtype,
culturally induced drinking processes and/or other environmental factors (e. g. family,
work) lead to alcohol use sufficiently cumulative to produce alcohol dependence.
More recently, though, Zucker (1994) suggested a need to differentiate this subtype
into finer distinctions to further account for different developmental trajectories.
Thus, Primary Alcoholism 1: Isolated Alcohol Abuse involves a single "incident" of
alcoholism often following an event such as marital dissolution. Primary Alcoholism
II: Episodic Alcoholism is a midpoint of the risk spectrum which begins to
approximate the clinical syndrome. Finally, Primary Alcoholism III:
Developmentally Cumulative Alcoholism is the clinical syndrome which is seen as

the product of alcohol specific variation and developmental processes.

25

As can be seen from the brief review above, although much progress has
occurred in the past decade regarding alcoholic classification systems, there is still
not sufficient agreement regarding the exact subtypes. However, one common thread
in most of the typologies reviewed involves the distinction between Antisocial (with
its earlier onset and apparent higher genetic basis) and Nonantisocial alcoholics.
Recently, it has been proposed that a subset of female alcoholics can similarly be
identified based on the levels of antisocial behavior (Zucker & Gomberg, 1993).
Zucker and Gomberg argued that although other comorbid diagnoses are more
common than Antisocial Personality Disorder in women, there has been a failure to
look at the occurrences of these disorders in a relative sense. For example, the
authors stated that although phobias show a strong association with alcoholism, their
comorbidity with alcoholism among women is not remarkable when compared to the
general population of women, or to alcoholic men. On the other hand, Zucker and
Gomberg pointed out that the incidence of Antisocial Personality Disorder is quite
rare in the general population of women, but relatively quite high in alcoholic
women.

While some studies have not found Antisocial Alcoholism in females (e.g.,
Bohman, Sigvardsson, & Cloninger, 1981), other more recent studies have provided
evidence for an antisocial subtype of alcoholism in women (Glenn & Nixon, 1991;
Hesselbrock et al, 1984; Lex, Sholar, Bower, & Mendelson, 1991). In addition,
Hesselbrock and Hesselbrock (1993) suggested that previous research showing
internalizing symptoms as more predictive of future alcohol problems in women may

be true when antisocial behavior is less severe in females. However, the authors

26

suggested that severe Antisocial Personality Disorder in females may more closely
resemble the linkage to alcoholism previously reported in only males. Thus,
additional research is needed into the relationship between early externalizing
behavior in young females and its later relationship with alcoholism.

Alcoholic Subtypes and its Relevance to the COA Limture

Clearly, the current research indicates the need to view alcoholism as a
heterogenous disorder. Therefore, distinguishing COAs based on even two subtypes
of parental alcoholism (Antisocial versus Nonantisocial) would be useful at this stage
of development for understanding alcoholic heterogeneity. As was pointed out
earlier, the failure to distinguish different subtypes of alcoholism may be one of the
important contributors to the contradictory findings among COA studies. The
evidence regarding alcoholic subtypes suggests different developmental trajectories
and causative factors (e.g. some subtypes have a greater genetic diathesis than
others). Thus, it would therefore seem to follow that COAs should differ in
significant ways based on the type of alcoholism their parents experience, due to the
different biopsychosocial factors impacting their development as well.

There is currently some evidence regarding the potential usage of alcohol
typologies in studies of COAs (Cloninger et al., 1981; Ellis, 1992, Ellis, Bingham,
Zucker, & Fitzgerald, 1996; Zucker, Ellis, & Fitzgerald, 1994a). In Cloninger’s
identification of Type I and Type II alcoholics described previously, efforts were also
made to look at the type of alcoholism expressed by the biological parents of their
COA sample. The authors reported that Type 2 alcoholism (with its higher genetic

component) was associated with both severe alcoholism and criminality in the

27

biological fathers of these men. On the other hand, Type 1 alcoholism was not.
Thus, Antisocial Alcoholics, in particular, may pass the same type of alcoholism onto
their male offspring (Ellis, 1992). Whether this might be through genetic or
environmental factors, or more likely a combination of the two, remains to be seen.

More recent investigations provide some evidence of the mechanisms by
which this risk may be transmitted even in the very early years of a COA’s life
(Ellis, 1992, Ellis et al., 1996; Zucker et al., 1994a). In these studies, young male
children (ages 3-5) of Antisocial Alcoholic (AAL) families experienced higher levels
of behavior problems than similar children in Nonantisocial Alcoholic (NAAL) or
Control families. Further analyses confirmed that different factors played a role in
the development of child externalizing behavior problems among the groups. In
AAL families, heritable factors predicted externalizing behavior in the young children
though this was not true for the other groups. This was in contrast to the NAAL
group in which marital conflict best predicted behavioral difficulties in those
children. Finally, only temperamental mismatch between parent and child predicted
externalizing behavior problems among children of Control families.

The results of these studies, along with the recent evidence showing the
relationship between antisocial behavior and alcoholism in women, suggest that girls
may also experience differences based on the type of alcoholism exhibited by their
parents. Identifying potential differences based on parental subtype, and the possible
environmental and genetic factors that lead to these differences, is important to
developing early prevention and treatment strategies, as well to improving the overall

understanding of alcoholism in women.

Statement of the Problem

Alcoholism is a heterogeneous, not homogeneous, disorder. One body of
evidence for its heterogeneity comes from the extant literature regarding subtypes of
alcoholism; the observed differences clearly suggest different developmental
pathways and different biopsychosocial processes in their creation. Although there is
not clear agreement regarding the final number, or nature, of these subtypes, there is
considerable knowledge about two of the more common developmental trajectories
that lead to differing alcoholisms (i.e. Antisocial versus Nonantisocial Alcoholism).

One weakness in the existing literature is the heavy focus on male alcoholics;
alcoholism in females was essentially ignored. However, there is now interest in
understanding alcoholism in women, as well as men. With new knowledge comes
the ability to understand whether female and male alcoholics differ from one another,
both in terms of clinical manifestations of the disorder(s) and etiology. Thus, some
current investigations are examining potential subtypes of alcoholism among women.
Antisocial Alcoholism is less common in women, whereas negative affectivity (e.g.
depression) is the more central component to female alcoholism. However, Zucker
and Gomberg (1993), in reviewing the literature on antisociality in women
alcoholics, concluded that there is a subset of female antisocial alcoholics with
current symptomatology and developmental trajectories similar to their male
counterparts. This points out the need for more thorough and comprehensive
investigation into this phenomenon.

In trying to understand the etiologies of various problems, a promising

methodological strategy is to study individuals who are at high-risk for the disorder.

28

29

There is a great deal of existing research that provides evidence that children of
alcoholics (COAs) are a high-risk population. COAs, both males and females, are
more likely to become alcoholic than children with nonalcoholic parents, although
this risk is higher for male COAs. In addition, male and female COAs have been
shown to be at risk for other biological, psychological, and social difficulties.
However, many COAs do not develop significant problems either in childhood, or as
adults. Thus, there has been an increased emphasis on trying to elucidate factors that
increase or decrease risk in COAs. The study of these individual differences in
COAs has already provided evidence for early developmental problems that may
ultimately prove to be pathways into later alcoholism.

Unfortunately, most of these investigations rely on samples of male COAs.
Those studies that include female COAs, are usually analyzed in a way that
homogenizes findings among the sexes, not permitting a more thorough
understanding of female COAs or of possible gender differences. The current
research aimed to focus on young female COAs in order to investigate early
developmental patterns that may lead to future problems as these girls mature. Such
data are important for understanding the developmental trajectories of potential

subtypes of alcoholism among women.

Hypotheses

The current study examined differences in developmental functioning for girls

in early and middle childhood who varied in COA status, and in exposure to an

alcoholic family environment. Among a sample of young female COAs (divided into

Antisocial and N onantisocial subtypes based on the father’s history of antisociality)

and a matched control sample of female children of nonalcoholic parents, the

following hypotheses were proposed:

1.

There would be differences between the girls in the three groups on
measures assessing the girls’ current behavior, health, IQ, and
academic achievement. Girls from Antisocial Alcoholic (AAL)
families would show lower levels of functioning than girls from
Nonantisocial Alcoholic (NAAL) families. Girls in the Control group
would be highest in their level of adaptation.

Age is a marker of increased exposure to a damaging environment.
On these grounds, older girls in the alcoholic families would function
at lower levels than the younger girls.

The recovery status of alcohol abuse in the parents would be a
significant factor, such that cessation of drinking problems at an early
enough age in the young female’s development would reduce negative
effects relative to girls whose parents continued to have problems with
alcohol; that is, girls in Recovering families would look more like the

group of Control girls on the outcome measures.

30

Method
Participants

Participants in the present study were 126 families with daughters ages three
through 11. The sample is a subset of families involved in the Michigan State
University - University of Michigan Longitudinal Study (Zucker, 1987; Zucker &
Fitzgerald, 1992a). This ongoing longitudinal project utilizes a population-based
sample of alcoholic men and their families, along with a contrast group of non—
substance abusing families drawn from the same neighborhoods where the alcoholic
families reside. Seventy eight families were Alcoholic, whereas 48 were
Nonalcoholic Controls. All families were Caucasian. The limited ethnic/racial
composition was dictated by the fact that census data in the area where data
collection took place indicated that other ethnic and racial groups would represent
less than 10% of the sample. Given the extensive literature demonstrating a
substantial relationship between patterns of alcohol/ substance involvement and
ethnic/racial status, and the fact that effective analyses for such differences could not
be undertaken with the proposed study sample size, it was decided to exclude such
variation, rather than have it contribute to error.

Families were invited to participate in a long term study of family health and
child development. All families received some payment for participation. Men were
recruited via both court contact and community canvass protocols. A network of
relationships with all district courts in a four-county area of mid-Michigan provided
access to all males convicted of drunk driving in this geographic locale during the

project recruitment period. In order to be eligible, men were required to have had a

31

32
blood alcohol concentration (BAC) of 0.15% (150mg/100ml) or higher at first

arrest,or a BAC of 0.12% if a history of prior alcohol-related arrests existed. At
initial recruitment, positive alcoholism diagnosis was first established using items
from the Short Michigan Alcohol Screening Test (SMAST; Selzer, Vinokur, & Van
Rooijen, 1975) shortly after recruitment; and again later with items from the NIMH
Diagnostic Interview Schedule (DIS-Version III; Robins, Helzer, Croughan, &
Ratcliffe, 1980). Fathers needed to meet Feighner diagnostic criteria (Feighner et
al., 1972) for either probable or definite alcoholism. Thereafter, DSM-IV diagnoses
for alcohol dependence or alcohol abuse were verified for each father.

At the time of recruitment, all Alcoholic fathers were required to have sons
between the ages of three and six, with whom they were living, and also to be
residing with the child’s mother. Mothers’ drinking status was assessed for
Alcoholic families, but the presence of alcoholism in these individuals was neither a
requirement or a basis for exclusion into the study.

The second strategy involved recruiting Alcoholic fathers out of the same
neighborhoods where the Drunk Driver Alcoholic fathers resided. These families
were accessed during neighborhood canvasses for Nonalcoholic (Control) families
(see below). Thus, they provided an ecologically comparable subset of high risk
families drawn out of the same social stratum as the Drunk Drivers, but where the
alcoholism was identified by way of community survey, rather than by way of legal
difficulty. These Alcoholic fathers also met Feighner criteria for probable or definite
alcoholism, had children and partners who met the same inclusion criteria as the

Drunk Driving group, but had no drunk driving or drug involved arrest record

33

occurring during the lifetime of the three to five year old male target child (MTC).

In addition to Alcoholic families, a group of community Control families was
recruited via door-to-door community survey techniques. These families were
recruited out of the same neighborhoods as the Alcoholic families, and were
homogeneous with them regarding the age of the MTC. An effort was also made to
match Control families with Alcoholic families on the basis of family socioeconomic
status by recruiting them from the same neighborhood in which the Risk family
lived. Canvassers initiated a door-to-door search a block away from the Alcoholic
family, staying within the same census tract, and screened for Nonalcoholic families
with a male child of appropriate age. However, in some cases, locating a
neighborhood Control proved impossible due to high levels of drug and/or alcohol
abuse among potential Control families living in these neighborhoods. In such cases,
the recruitment moved to an adjacent neighborhood. Occasionally, it was also
necessary to go even more broadly afield in order to locate another socio-
demographically comparable community in which to continue the search.

Families are assessed at three year intervals so that Wave 1 involves children
of ages 3-5, Wave 2 of children ages 6-8, Wave 3 of children ages 9-11, etc.
Beginning at the second wave of data collection data for the MTC, data were also
collected from a female sibling in families where there was a daughter between the
ages of three and 11. When there were multiple female siblings in the family, the
female target child (FTC) chosen for inclusion was alternated among families
between an older or younger sibling to the MTC. Inclusion criteria for this FTC

specified that she be the biological child of both natural parents of the MTC (some

34

families had experienced divorces and remarriages by the time this second wave of
data were collected).

All families were able to continue their participation in the larger study, even
if they declined their daughter’s participation. However, all families who had
eligible FTCs, in fact, agreed to have their female child participate. The data in the
present study were from the families with an FTC within the ages of three through
eleven. These data were from the FTC’s first data collection wave, although they
were acquired during various time waves of the MTC’s data collection protocol.
Thus, the current study involves only cross-sectional, rather than longitudinal data.
As was the case when originally recruited into the study, neither parent in Control
families met DSM-IV criteria for Alcohol Abuse or Alcohol Dependence.

Procedure

Data were collected by trained project staff who were blind to family
alcoholic status. Due to the large amount of data collected from each family, a
number of contacts with the family were necessary. This number differed, dependent
on the age of the MTC and FTC. The visits involved approximately 9-10 hours of
contact time with each parent, and seven hours of contact time with each target child.
Contacts included questionnaire sessions, semi-structured interviews, and interactive
tasks. Most of the contacts occurred in the families’ homes, although one contact
occurred on the university campus (for interactional assessments). Special
arrangements were made to collect data from families that relocated from the area
since the inception of the study. However, an effort was made to minimize any

differences between data collection in these families and the families whose data were

35

collected in the usual manner. The data for the current project only involve those
measures needed for testing the study’s hypotheses.
Measures

Parent Measures

Background Demographic Information. Information on demographics came
from a questionnaire assessing education, occupation, family income, parents’
occupation, and marital history. Socioeconomic status (SES) of participants was
calculated using the Duncan TSE12 Socioeconomic Index (Steven & Featherman,
1981), an occupationally-based measure of social prestige. Significant evidence
exists in the sociological literature to suggest that occupation, not income or
education, is the optimal indicator of SES and that the perceived prestige of an
occupation best captures its underlying socioeconomic dimension (Mueller & Parcel,
1981). An average of the two parent’s Duncan score was used as the family’s SES.
Lowest possible Duncan scores were used for families where neither parent was
employed.

Pgrerga} Alcoholifl. As described previously, all parents completed the
Short Michigan Alcohol Screening Test (SMAST; Selzer et al., 1975) and the DIS-
Version 111 (Robins, Helzer, Croughan, & Ratcliffe, 1980). The SMAST is a well
validated screening inventory used to assess alcohol problems. It consists of 13 items
that are answered with either a "Yes" or "No" response.

The DIS-Version III is a structured interview that allows trained lay
interviewers to gather extensive information about physical, alcohol-related, and

drug-related symptoms, as well as other areas of mental health. This information can

36

then be used to make diagnoses by way of popularly used nosological systems.
Although the entire DIS was administered to each parent, only the information from
the alcohol use section was used in this study.

The Drinking and Drug History Questionnaire (Appendix A; Zucker,
Fitzgerald, & Noll, 1990) was also administered to the parents. This instrument
gathers information from the subject about his/her use of alcohol and other drugs.
Only information from the alcohol section was used in the present study. This
section focuses on the amount of alcohol usage in the past six months. In the
Lifetime Version of this instrument (given the first time the family entered into the
study), the questionnaire also inquires about the largest amount of alcohol consumed
during a 24—hour period at any point in the participant’s life. At later tirnewaves, the
alcohol section assessed use in the last three years, in addition to the last six months.
Finally, the instrument asks the participant whether s/he has experienced various
problems as a result of alcohol usage, and if so, the frequency of these problems
(during one’s lifetime for the Lifetime Version, and during the last one year and last
three years for other versions).

A diagnosis regarding mother’s and father’s alcoholism was made by a trained
clinician using DSM-IV criteria based on information provided by the parent on the
Drinking and Drug History Questionnaire, the SMAST, and the DIS - Version 111.
Diagnoses were made over the following periods: lifetime, past three years, and the
past year. A positive lifetime diagnosis for alcoholism was made if the individual
met at least DSM-IV Alcohol Abuse criteria during their children’s lives. In the

current sample, 85 of the 126 families had a father meeting such criteria. Of these

37

85 families, seven fathers met alcohol abuse/dependence criteria, but all drinking
problems had ceased by the age of 22, as well as before the birth of any child.
These seven families fit a Developmentally Limited Alcoholism subtype described by
Zucker (1994) and were classified as Control families, rather than Alcoholic families,
because of the lack of significant alcohol problems during adulthood. The
information regarding diagnoses for the past three years was used in the analyses
examining potential differences in Recovering versus N on-Recovering alcoholic
families.

Antisocial behavior. The Antisocial Behavior Inventory (ASB; Appendix B;
Zucker & Noll, 1980; Ham, Zucker, & Fitzgerald, 1993) was used to assess
antisocial behavior in the fathers. This 46-item inventory is a revision of an earlier
antisocial behavior inventory used in the Rutgers Community Study (Zucker &
Barron, 1973; Zucker & Fillmore, 1968). The revised version contains items that
are also salient for adult antisocial activity. Each participant responds to the
frequency that he has engaged in various "adventures" during his life (e.g. "lied to a
teacher or principal", "taken part in a robbery") using the following scale: (a)
"Never" - never done this in his life, (b) "Rarely" - once or twice in his life, (c)
"Sometimes" - three to nine times in his life, and (d) "Often" - more than ten times
in his life. The lifetime version of this measure then assesses antisocial behavior as a
child, and as an adult.

A series of reliability and validity studies (Zucker, Noll, Ham, Fitzgerald, &
Sullivan, 1994) with different populations has shown adequate test-retest reliabilities

(0.91 over four weeks) and internal consistency (alpha = 0.93). The instrument also

38

differentiates between individuals with long histories of antisocial behavior (e.g.
prisoners) versus individuals with minor offenses versus university students. Finally,
the instrument has shown the ability to differentiate alcoholic from nonalcoholic adult
males (Fitzgerald, Jones, Maguin, Zucker, & Noll, 1991).

Alcoholic subtype. In order for FTCs to be identified as offspring of
Antisocial Alcoholics (AALs) or NonAntisocial Alcoholics (NAALs), fathers were
classified as AALs or NAALs. Fathers’ scores on the ASB were summed separately
for childhood (Items 1-18) and adult domains (Items 19-46). By using this method, a
pattern of sustained antisociality, rather than one that is more time-limited,
distinguished AALs from NAALs (Zucker, Ellis, & Fitzgerald, 1994b, Zucker, Ellis,
Fitzgerald, Bingham, & Sanford, 1996). In order to be qualified as an AAL, the
father had to have a score of 10 or higher during both childhood and adulthood. In a
previous study (Zucker et al., 1996), this typing strategy has been successful in
distinguishing AALs from NAALs regarding age of onset, severity, number, and life
course of alcohol problems, measures of social adaptation, amount and severity of
other psychopathology, and salience of family history load for alcoholism. Those
alcoholic fathers not meeting this cut-off point were classified as N AALs. Fathers
not abusing alcohol were considered to be Control subjects regardless of their scores
on the ASB.

Child Measures

Female Target Child’s Current Behavior. Each parent completed the

Achenbach Child Behavior Checklist - Parent Version (CBCL; Achenbach &

Edelbrock, 1983). The CBCL is a factor-analytically derived parent report form

39

used to descriptively classify children for research and clinical purposes. Parents
rated their children during the past six months on a number of behavior items using a
scale of "0" (Not True), "1" (Somewhat or Sometimes True), and "2" (Very True or
Often True). The CBCL yields scores on two Broadband factors reflecting
Extemalizing and Intemalizing behavior. It also provides an overall index of child
behavior problems called the Total Behavior Problem score, and a Social
Competency score. Finally, various N arrowband factors are also defined
(Withdrawn Behavior, Somatic Complaints, Anxious/Depressed, Social Problems,
Thought Problems, Delinquent Behavior, and Aggressive Behavior).

The CBCL has been normed and standardized on children aged four to sixteen
(Achenbach & Edelbrock, 1983). Achenbach and Edelbrock demonstrated test-retest
reliability of item scores on the CBCL ranging from 0.95 at a one-week interval, to
0.84 at a three-month interval. Parent agreement on the item scores was 0.99.
Similar reliabilities were established on scale scores and Total Problems with one-
week test-retest reliabilities of 0.89. The median parent agreement on scale scores
was 0.66. Adequate construct validity was established through correlations between
CBCL scores and scores on other measures of child behavior problems. External
validity was also demonstrated to be adequate.

In addition to parent ratings, teachers also rated the FTC’s current behavior
using the Child Behavior Checklist - Teacher Form (TRF; Achenbach & Edelbrock,
1983). This form is similar to the CBCL except that teachers rate the child’s
behavior only for the previous two months. Some of the items are also changed to

reflect behavior about which teachers have more ability to report. Factor analysis of

40

the TRF yielded Broadband Internalizing and Extemalizing factors like those on the
CBCL. Narrowband factors were also derived. In the current study, the youngest
aged girls (i.e. those not yet attending school) did not have TRFs completed.

Intellectual Functioning. Current general intellectual functioning for FTCs,
ages six or older, was measured with the Wechsler Intelligence Test for Children -
Revised (WISC-R; Wechsler, 1974). The WISC-R, a commonly used intelligence
measure, was developed for use with children ages six through sixteen. It consists of
twelve subtests with six of them assessing Verbal skills, and six of them assessing
Performance skills. Scaled scores are calculated for each subtest. In addition, a
Verbal IQ, a Performance IQ, and a Full Scale IQ score were calculated.

The WISC-R was normed on groups which are representative of the US.
population of children (Wechsler, 1974). The average internal reliability coefficients
across the entire age range for the Verbal, Performance, and Full Scale IQs were
0.94, 0.90, and 0.96, respectively. Reliabilities for individual subtests were also
good, with the average coefficients ranging from 0.77 to 0.86 for the Verbal tests,
and from 0.70 to 0.85 for Performance tests. Test-retest reliabilities were also
obtained with results similar to those obtained for internal consistency. Adequate
validity of the instrument has been established through correlations with other
individually-administered intelligence tests.

Intellectual functioning in FTCs below the age of six was assessed with the
Third Revision (Form L-M) of the Stanford-Binet Intelligence Scale (Stanford-Binet;
Terman & Merrill, 1973). The Stanford-Binet, another commonly used measure of

intelligence, consists of several subtests designed to measure general mental

41

adaptability. It is used with children as young as two, as well as with adults. An
overall IQ was obtained by calculating the subject’s obtained Mental Age and
comparing it to his/her Chronological age. In the current study, the IQ calculation
was based upon the 1972 norms because they are the latest ones available for this
instrument.

Although different IQ measures (Stanford-Binet vs. WISC-R) were
administered depending on the age of the FTC, scores from these two measures are
generally quite similar, with correlations between Full Scale IQ on the WISC-R and
the Stanford-Binet IQ reported to be 0.82 (Sattler, 1982). The only psychometric
difference between the two measures is the standard deviations; the WISC-R has a
standard deviation of 15 while the Stanford-Binet has one of 16. On these grounds,
Stanford-Binet and WISC-R IQs were standardized using each measure’s own mean
and standard deviations, then pooled and used in the analyses. That is, a z-score was
calculated for each girl who had an IQ from the Stanford-Binet by subtracting 100
from her obtained IQ, and then dividing this number by 16 (z = IQ - 100 / 16). For
each girl with an IQ from the WISC-R, a z-score was calculated by subtracting 100
from her obtained IQ, and then dividing this number by 15 (z = IQ - 100 / 15).
These calculated z-scores were then used in subsequent analyses.

Academic Achievement. The Wide Range Achievement Test - Revised
(WRAT-R; Jastak & Wilkinson, 1984) was used to assess current academic
achievement in the FTCs. The WRAT-R was designed to assess a child’s skill in
basic academic coding tasks. The test consists of three subtests (Reading, Spelling,

and Arithmetic) and yields standard scores, percentiles, and grade ratings. It was

42

standardized on a national sample of 5600 individuals ranging in age from 5 years, 0
months to 74 years. It is a widely used instrument with adequate reliability and
validity. In the current study, the WRAT-R was only given to school-aged FTCs (i.e.
those six years of age and older) because its usage is inappropriate for younger ages.

Health Problems. The Child Health and Developmental History Questionnaire
(Appendix C; Zucker & Fitzgerald, 1992b) was completed by the mother, or primary
caregiver, of the FTC. This instrument was created by the MSU-UM Longitudinal
Study and is intended for children aged six and older. Thus, again, the youngest
FTCs in this study did not have data available for analysis.

Questionnaire items are structured, and as specific as possible, to allow the
parent to more reliably answer historical questions. The questionnaire focuses on the
following areas: growth and development, child’s health, social development, family
background information, and school history. In the current study, the following
variables were calculated from participant responses: Number of Developmental
Services Received (# of "Yes" responses to questions Q1A - QlE in Section II),
Number of Hospitalizations (# of hospitalizations recorded on Q4 in Section IV),
Number of Accidents (# of accidents recorded on Q5 in Section IV), Number of
Sensory Problems (Total # of "Yes" responses to Q9, Section IV; Q2-Q5, Section
VII; Q2-Q5, Section VIII; and Q2, Section IX), Number of Different Medications
Taken (# of "Yes" responses to Q3a-Q3l, Section IV, not including Q3i), Elimination
Problems ("Yes" responses to Q2 and Q3, Section VI), Height (Q3, Section III),
Weight (Q4, Section 111), General Sleep Problems (Sum of Items Q2a-Q2n, Section

V), and Sleep Apnea Problems (Sum of Items Q2a, Q2c, and Q2j, Section V).

Results
Missing and Problemgtic Dfl

On rare occasions during data collection, an instrument, or part of an
instrument was coded as "suspect," or problematic, by the administrator. This
occurred when testing conditions were so poor that the administrator was concerned
the data obtained did not accurately represent the person’s functioning, or because the
participant was uncooperative even though s/he completed the instrument. In the
present study, only two child participants had a portion of their data coded in this
manner. The instrument in question in each case was the IQ measure. These two
individual’s scores were clearly outliers when plotted against other scores on the
basis of their status. It was therefore decided that these two pieces of data should be
treated as missing data.

For a small number of participants, data were missing on several of the
measures, although the same participant family typically was not missing data from
more than one instrument. For the intelligence measures (Stanford-Binet and WISC-
R), since there were only four percent (five out of 126 participants) with missing
data, data estimates were calculated using least squares regression analyses run on
available non-missing data. Stepwise entry was used to build the models. Since the
purpose of the study was to examine alcohol risk group differences and age
differences in the variables being estimated, and since strong evidence already exists
that study data vary substantially (Zucker et al., 1996; Bingham et al., 1996),
missing data were estimated separately by family Risk Group (AAL, NAAL,

Control) and FTC Age Cohort (ages 3-5, ages 6—8, ages 9-11). The predictor

43

44

variables used were paternal and maternal IQ scores, paternal and maternal education
levels, and Extemalizing, Internalizing, and Total Behavior Scores on the Father and
Mother CBCL, and the Teacher TRF.

Missing data estimates were also performed for the eight Narrowband factors,
two Broadband factors, and Total Behavior Problems of the Mother and Father
CBCLs, as again, the amount of data missing was not very great (8.6% of the
sample was missing father data only, 1.6% of the sample was missing mother data
only, and 6.3% of the sample was missing both parents’ data). Analyses similar to
the ones described for the IQ measures were run. However, the predictor variables
in these analyses were FTC WRAT-R Arithmetic, Spelling, and Reading scores,
scores from Total Behavior Problems, the two Broadband, and eight Narrowband
scales of the Teacher TRF, and scores from Total Behavior Problems, and the two
Broadband and eight Narrowband scales of the non-missing parent CBCL. For
Mother data, no regression equations with the current predictors could be identified
on the Anxious/Depressed, Social Problems, Attention Problems, and Aggressive
Behavior scales for Control participants only. For Father data, no regression
equations could be identified for Control participants on the Aggressive Behavior
scale; for NAALs on the Somatic Complaints, Attention Problems, Internalizing, and
Total Behavior Problems scales; and for AALs on the Thought Problem and
Delinquent Behavior scales. For these data, the mean of each scale for the respective
Risk Group and Age Cohort was used as the missing data point.

Due to the large amount of missing data on the WRAT—R, the Teacher TRF,

and the Child Health and Developmental History Questionnaire, estimates were not

45

performed for these measures. Data were missing here because these instruments
were not part of the protocol for the youngest girls (ages 3-5) since their ages were
inappropriate for the instruments. All analyses involving these measures are only
performed on families with girls assessed between the ages of six and eleven.

Following data estimation, the estimated variables were compared to the
original variables to ensure that no bias had occurred as a result of estimation
procedures. To test this possibility, a stacked two-group design using LISREL 8.1
(Joreskog & Sorbom, 1993) was used to compare the mean and covariance structures
of the estimated and original variables (Bingham & Crockett, in press) with all
parameter estimates invariant. IQ, and each parent’s rating of Total Behavior
Problems on the CBCL, were done in one comparison (Goodness of Fit Index =
0.99 [X2 (6) = 2.31, p = 0.89]). Each parent’s ratings on the two Broadband
factors of the CBCL were done on another comparison (GFI = 0.99 [_)_(_2 (10) =
5.22, p = 088]). Finally, a third comparison was done using the eight Narrowband
scales of each parent’s CBCL rating (GFI = 1.00 [X2 (136) = 28.21, p = 1.00).
The high GFI indices on all three comparisons provided evidence of extremely good
fit. They indicate that the central tendency, dispersion of the estimated variables,
and the patterns of covariation among the variables were not altered significantly by
the data estimation procedure.

WW

Table 1 presents the number of AAL, NAAL, and Control families across the

three Age Cohorts in this study. As can be seen in the table, the figures indicate that

group membership percentages of participant families were approximately equal

46

Table 1. Number of Families with Girls in AAL, NAAL, and Control Groups
Across Ages 3-11 (N = 126)

 

 

 

 

RISK GROUP AGE COHORT
TOTALS
AGE COHORT m MAJ; M
Ages 3-5 13 (23%) 25 (44%) 19 (33%) 57
Ages 6-8 8 (20%) 16 (40%) 16 (40%) 40
Ages 9—11 6 (21%) 10 (34%) 13 (45%) 29
RISK GROUP TOTALS 27 51 48

 

Note. Percentages in the table are the percentage of Risk Group families for that
FTC age period (i.e. individual cell 11 / Age Cohort r_1)

47

across Age Cohorts. Thus, potential interactions between group membership and age
cohort that might be relevant to substantive hypotheses (i.e. that differences between
Risk Groups on variables was due to an overweighing of families of a Risk Group in
certain Age Cohorts), can be ruled out as potential confounds.

To control for Type I error, MAN OVAs were conducted within each of the
major domains of study investigation. A Wilks multivariate analysis of variance
(MAN OVA) for Risk Group differences was conducted on the following
demographic variables: FTC age, maternal age, paternal age, maternal years of
education, paternal years of education, annual family income, and family SES.
Demographic information on the sample is presented in Table 2. The MANOVA
showed significant Risk Group effects upon demographic variables LE (14, 234) =
3.19, p < .01]. Univariate analyses of variance (ANOVAS) showed significant
group differences for Maternal Education, Paternal Education, Family Income, and
Family SES (see Table 2).

Post-hoe comparisons using the Student-Newman-Keuls Test (SNK) with
alpha level set at 0.05 were used to identify which of the three groups differed (see
Table 2). Mothers in AAL families had significantly less education than did mothers
in Control families, while fathers in AAL families had less education than fathers in
both NAAL and Control families. The annual family income in AAL families was
lower than the income in either NAAL or Control families, and the income in NAAL
families was significantly lower than the income in Control families. Finally, SES

was significantly lower in AAL families than in Control families.

48

Table 2. Demographic Characteristics of AAL. NAAL. Ed Control Families with
Fertile Children

 

RISK GROUP
AALs NAALs Controls
(1.1=27) (I_1=51) (L1=48)
VARIABLE Mean (SD) Mean (SD) Mean (SD) Univariate E

 

[Multivariate F (14,234) = 3.19, p < .01]

FTC Age 6.78 (2.37) 6.43 (2.72) 7.12 (2.30) 0.95

Maternal Age 33.85 (3.77) 34.89 (4.21) 34.97 (4.56) 0.69

Paternal Age 37.67 (6.18) 36.17 (5.27) 36.29 (4.72) 0.79

Maternal Education 12.70 (1.68) 13.86 (2.06) 13.75 (2.26) 3.07'a
(in years)

Paternal Education 12.48 (1.65) 13.90 (2.24) 14.73 (2.26) 9.58"“
(in years)

Annual Family 30.98 (19.27) 43.87 (20.99) 52.76 (22.68) 9.06”"bc
Income

Family SES 296.31 (114.01) 359.16 (153.89) 396.90 (149.74) 4.18"

 

Note. Annual Family Income is represented in thousand dollar units

' p < .05 " p < .01 [if = (2,123) for all Univariate Tests]
" AALs < Controls b NAALs < Controls C AALs < NAALs

49
Child Outcome Variables

Intellectual Functioning

Table 3 shows means and standard deviations for FTC IQ scores. A 3 (Risk
Group) X 3 (Age Cohort) ANOVA revealed a significant main effect for Risk Group
[F (2,117) = 4.49, p < .05]. Neither a significant Age Cohort effect, or a
significant interaction, were found. Post-hoe comparisons using the SNK showed
that girls in AAL families had significantly lower IQs than did girls in Control
families.

Academic Achievement

Table 4 shows means and standard deviations for WRAT-R standard scores.
A 3 (Risk Group) X 2 (Age Cohort) MANOVA revealed a significant main effect for
Age Cohort [F (3,60) = 3.25, p < .05]. Although the means for Risk Group were
in the predicted direction, these differences were not statistically significant. There
was also no significant interaction observed.

Univariate ANOVAS for the Age Cohort factor showed significant group
differences on the Reading and Spelling subtests, but not the Arithmetic subtest of the
WRAT-R. For Reading and Spelling, older girls scored significantly higher than
younger girls (see Table 4).

Child Behavior Problems

Table 5 displays results from analyses on CBCL Total Behavior Problems and
the two Broadband factors, while Table 6 shows results from CBCL Narrowband
factors. For CBCL Total Behavior Problems, a 3 (Risk Group) X 3 (Age Cohort) X

2 (Parent Reporting) ANOVA was performed, while separate 3 (Risk Group) X 3

50

Table 3. Z-Scores for IntellectuaLPerformgnce of Girls in AAL. NAAL. and Control
Families Across Ages 3-11

 

AGE
COHORT

Ages 3-5
(n=57)

Ages 6—8
(E=40)

Ages 9-11
(L1=29)

RISK GROUP
Totals

 

RISK GROUP
AALs NAALs
(E=27) (2:51)

Mean (SD) Mean (SD)
0.25 (1.19) 0.49 (0.84)

0.19 (0.91) 0.42 (0.98)

~0.01 (0.66) 0.89 (0.87)

0.17 (0.98) 0.55 (0.89)

Univa_riate ANOVA

AGE COHORT
TOTALS

Controls
(11:48)

Mean (SD) Mean (SD)
0.94 (0.78) 0.59 (0.93)

0.66 (0.65) 0.47 (0.57)

0.79 (0.85) 0.66 (0.87)

0.80 (0.75)

E(2,117) for Risk Group = 4.49"3
E(2,117) for Age Cohort = 0.30
E(4,117) for Risk Group X Age Cohort = 0.58

 

Note. To allow pooling of Stanford-Binet (ages 3-5) and WISC-R (ages 6-11) IQs,
these data were converted to z-scores (See text in Method section)

'p<.05

’ AALs < Controls

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52
(Age Cohort) X 2 (Parent Reporting) MANOVAS were performed for the two CBCL

Broadband factors and the eight Narrowband factors. None of the analyses showed
main effects or interactions with the Parent Reporting factor, thus the means and
standard deviations reported in Tables 5 and 6 are aggregated across both parents.

As can be seen in Table 5, the ANOVA for CBCL Total Behavior Problems
revealed a significant main effect for Risk Group [F (2,234) = 4.20, p < .05]. No
other main effect or interactions were significant. Post-hoe analysis using the SNK
showed that AALs and NAALs had significantly greater Total Behavior Problems
than Controls. NAALs and AALs did not differ.

The MANOVA on CBCL Broadband factors showed significant main effects
for Risk Group and Age Cohort (see Table 5). Univariate Es showed that these
effects were only significant for Extemalizing Behavior Problems [Risk Group F
(2,234) = 4.85, p < .05; Age Cohort E (2,234) = 4.32, p < .05) and not for
Internalizing problems. Post-hoc analyses using the SNK showed that AAL and
NAAL girls had more Extemalizing Behavior Problems than Controls. Again,
NAALs and AALs did not significantly differ. Post-hoe tests also revealed that girls
in the younger two groups (ages 3-5 and 6-8) had more Extemalizing problems than
the older girls (ages 9-11).

Significant main effects for Risk Group and Age Cohort were also found on
the MAN OVA for CBCL Narrowband factors (see Table 6). Univariate Es for the
Risk Group effect showed a significant difference for the Somatic Complaints E
(2,234) = 3.07, p < .05] and the Social Problems scale [E (2,234) = 4.10, p <

.05]. However, post-hoe analyses revealed no significant differences between any

53

Table 5. Parents’ Ratings of Their Daughters’ Behavior Using CBCL Total Behavior
Problems fld Broadband Factors in AAL. NAAL, amd ContLrol Families

Across Ages 3-11 (T-Scores)

 

 

 

RISK GROUP AGE COHORT
TOTALS
AALs NAALS Controls
AGE (p=27) (p=51) m=48)
VARIABLE COHORT Mean (SD) Mean (SD) Mean (SD) Mean (SD) r_1
Total Beh. 3-5 52.19 (6.60) 49.86 (6.94) 48.45 (7.07) 49.92 (6.99) 57
Problems 6-8 50.81 (5.95) 52.16 (8.21) 46.31(10.25) 49.55 (9.34) 40
9-11 49.58 (8.54) 47.35 (6.75) 46.88 (8.71) 47.60 (7.98) 29
Risk Group Totals 51.20 (6.84) 50.09 (7.74) 47.31 (8.64)
Extemalizing 3-5 53.92 (6.72) 51.02 (7.50) 51.03 (7.23) 51.68 (7.28) 57
Behavior 6-8 52.88 (6.78) 55.09 (8.21) 48.00 (9.01) 51.81 (8.80) 40
9-11 49.58 (7.38) 48.85 (5.84) 46.88 (9.22) 48.12 (7.78) 29
Risk Group Totals 52.65 (6.97) 51.87 (7 .74) 48.90 (8.55)
Internalizing 3-5 49.65 (6.88) 47.50 (6.81) 46.42 (7.83) 47.63 (7.22) 57
Behavior 6-8 48.50 (5.55) 49.91 (9.42) 48.09 (8.72) 48.90 (8.44) 40
9-11 51.33 (8.40) 48.35 (8.74) 50.00 (8.56) 49.71 (8.51) 29
Risk Group Totals 49.69 (6.84) 48.42 (8.08) 47.95 (8.30)

 

ANOVAS Ed MAN OVAS

Variable

Total Problems

Multivariate Es

Univariate Es
Parent (1,234) = 1.87
Risk Group (2,234) = 4.20""
Age Cohort (2,234) = 1.44

Risk Group (2,234) = 4.85"”
Age Cohort (2,234) = 4.32‘cd

Risk Group (2,234) = 0.72

Broadband Parent (2,233) = 0.83
Risk Group (4,466) = 3.05‘
Age Cohort (4,466) = 6.19"
Extemalizing
Behavior
Internalizing
Behavior

Age Cohort (2,234) = 1.20

 

Note. Means and Standard Deviations are aggregated across both Parents.
None of the Multivariate or Univariate interactions were significant.

‘p<.05 "p<.01

‘ AALs > Controls

” NAALS > Controls

° Ages 3-5>Ages 9-11d Ages 6-8 > Ages 9-11

54

Table 6. Parents’ Ratings of Their Daughters’ Behavior Using CBCL Narrowband Factors
in AAL, NAAL. and Control Families Across Ages 3-11 (T-Scores)

 

 

RISK GROUP AG]: CI‘JHORI

 

 

AALs N AALs Controls TOTALS
AGE m=27) (r_1=51) m=48)
VARIABLE COHORT Mean (SD) Mean (SD) Mean (SD) Mean (SD) _r_1
Withdrawn 3-5 52.04 (2.78) 54.26 (5.00) 53.71 (5.17) 53.57 (4.70) 57
6-8 53.00 (3.65) 53.38 (4.24) 53.09 (5.18) 53.19 (4.49) 40
9-11 53.92 (5.79) 54.05 (5.21) 53.46 (5.67) 53.76 (5.45) 29
Risk Group Totals 52.74 (3.87) 53.94 (4.78) 53.44 (5.26)
Somatic 3-5 54.19 (4.81) 52.72 (3.49) 51.92 (2.36) 52.79 (3.60)1 57
Complaints 6-8 53.69 (4.91) 53.12 (4.34) 53.84 (4.64) 53.52 (4.43) 40
9-11 57.00 (7.05) 53.35 (5.81) 53.24 (4.90) 54.59 (5.76)l 29
Risk Group Totals 54.67 (5.45) 52.97 (4.26) 53.26 (4.13)
Anxious/ 3-5 52.85 (4.40) 51.54 (2.51) 51.79 (3.31) 51.92 (3.29) 57
Depressed 6-8 51.25 (2.02) 54.75 (5.80) 52.56 (5.26) 53.17 (5.17) 40
9-11 52.58 (4.70) 52.20 (4.03) 53.38 (5.32) 52.81 (4.73) 29
Risk Group Totals 52.31 (3.92) 52.68 (4.30) 52.48 (4.60)
Social 3-5 57.08 (7.92) 53.10 (4.70) 52.24 (3.18) 53.72 (5.50) 57
Problems 6-8 54.38 (6.10) 53.78 (4.85) 53.06 (5.98) 53.61 (5.53) 40
9-11 53.92 (5.90) 52.05 (4.45) 52.08 (5.25) 52.45 (5.10) 29
Risk Group Totals 55.57 (7.04)"b 53.11 (4.70)” 52.47 (4.80)a
Thought 3-5 54.08 (5.80) 52.42 (4.81) 51.87 (3.99) 52.61 (4.83) 57
Problems 6-8 51.25 (2.72) 52.81 (4.95) 52.00 (4.75) 52.18 (4.49) 40
9-11 52.17 (3.56) 52.45 (5.41) 50.88 (3.28) 51.69 (4.18) 29
Risk Group Totals 52.81 (4.71) 52.55 (4.93) 51.65 (4.07)
Attention 3-5 53.92 (4.60) 52.54 (3.55) 52.32 (3.33) 52.78 (3.76) 57
Problems 6-8 51.94 (2.52) 53.31 (3.57) 52.59 (5.17) 52.75 (4.12) 40
9-11 53.17 (5.42) 51.20 (2.14) 53.19 (5.48) 52.31 (4.58) 29
Risk Group Totals 53.17 (4.32) 52.52 (3.38) 52.53 (4.57)
Delinquent 3-5 55.31 (5.97) 54.46 (4.43) 53.24 (4.05) 54.25 (4.81) 57
Behavior 6-8 55.06 (4.43) 56.63 (6.64) 53.34 (4.57) 55.00 (5.61) 40
9—11 54.75 (6.69) 52.20 (3.94) 53.19 (5.48) 53.17 (5.28) 29
Risk Group Totals 55.11 (5.63) 54.70 (5.33) 53.26 (4.60)
Aggressive 3-5 55.15 (5.79) 53.84 (4.64) 53.79 (5.32) 54.12 (5.14)"2 57
Behavior 6-8 54.19 (4.85) 56.44 (6.49) 52.84 (5.21) 54.55 (5.85)2 40
9-11 52.25 (3.41) 51.80 (3.66) 52.23 (3.95) 52.09 (3.69)l 29
Risk Group Totals 54.22 (5.12) 54.25 (5.36) 53.05 (4.94)

Multivariate F
Parent X Risk Group (16,454) = 0.56
Parent X Age Cohort (16,454) = 0.96
Risk Group X Age Cohort (32,839) = 1.27
Parent X RG X AC (32,839) = 0.77

Parent (8,227) = 1.62
Risk Group (16,454) = 1.99‘
Age Cohort (16,454) = 2.08"

 

o . e re g a r re 8.
Means with the same superscript differ at p < .05 (Student-Newman—Keuls Test) and
also are the only variables in which Univariate Es were significant for that factor.
’o<.05 "p<.01

55

two groups on the Somatic Complaints scale. For the Social Problems scale, the
SNK showed that AALs had greater problems in this area than Controls and NAALS.
Controls and NAALS did not differ.

Univariate Es for the Age Cohort effect showed significant differences
between groups on the Somatic Complaint [E (2,234) = 3.53, p < .05] and
Aggressive Behavior scales [E (2,234) = 4.08, p < .05]. Post-hoe analyses showed
that girls ages 3-5 had less problems than girls ages 9-11 on the Somatic Complaints
scale, while girls ages 3-5 and ages 6-8 had more problems than girls ages 9-11 on
the Aggressive Behavior scale.

Although there was not a significant main effect for which parent was rating
the FTC in any of the above analyses, nor any interactions with the Parent factor,
mother and father ratings are not completely independent of the other two factors
(i.e. Risk Group and Age Cohort). In order to rule out whether the significant Risk
Group and Age Cohort main effects were due to the paired nature of the Parent
factor within Risk Group, ANOVAS and MANOVAS were run using a nested design.
None of these tests were significant demonstrating that the Risk Group and Age
Cohort effects were not attributable to the fact that parent ratings were not
independent.

Finally, a 3 (Risk Group) X 2 (Age Cohort) ANOVA, using Teacher TRF
Total Behavior Problems as the dependent variable, showed no significant findings.
Similarly, separate 3 (Risk Group) X 2 (Age Cohort) MANOVAS for the two TRF
Broadband Factors, and the eight TRF Narrowband factors, yielded no significant

differences for main effects or interactions.

56
Child Health Issues

Since the Child Health and Developmental History was not administered to all
girls ages 3-5, and also was missing for a smaller number of older girls as well,
statistical power for these analyses was lower. Also, the incidence rate for the health
issues reported was very low, with little variability. Nevertheless, factorial (Risk
Group X Age Cohort) MANOVAS and ANOVAS were run on the following
variables: Number of Developmental Services Received, Number of Hospitalizations,
Number of Accidents, Number of Sensory Problems, Number of Different
Medications Taken, Elimination Problems (bedwetting or soiling), Height, Weight,
General Sleep Problems, and Sleep Apnea Problems. No significant effects were
found in any of these analyses. In addition, Chi-Square analyses for Risk Group and
Age Cohort, examining possible differences in presence or absence of Elimination
Problems, and presence or absence of Hospitalizations or Accidents, showed no
significant effects.

The Efffects of R_ecoverv from Alcohol Problems

In order to assess possible effects of remission of alcohol problems upon
child functioning, Alcoholic families were classified into Recovering and Non-
Recovering families based on whether the father met DSM-IV criteria for Alcohol
Abuse or Dependence within the last three years. Of the 51 NAAL families, 15
fathers no longer experienced an alcohol diagnosis within three years of the FTC data
collection. Nine of the 27 AAL families no longer had a father experiencing an
alcohol diagnosis within the past three years.

It should also be noted that none of the fathers in the Control families

57
developed an alcohol diagnosis. The following ANOVAS and MAN OVAS were run

on only Alcoholic families in order to look for possible changes resulting from the
remission of alcohol problems. Since there was a very small number of subjects in
each Age Cohort group (e. g. only three Recovering NAAL 6-8 year olds and two
Recovering AAL 9-11 year olds), age differences could not be analyzed. When
significant main effects for Recovery Status were found, planned comparisons with
Control families were run in order to test if there were differences between Control,
Recovering, and Non-Recovering families.

A 2 (Risk Group) X 2 (Recovery Status) MAN OVA was performed for
demographic variables (see Table 7). As can be seen in the table, this analysis
showed significant multivariate main effects for both Risk Group and Recovery
Status. There was no significant multivariate interaction. Univariate E analyses
showed AAL families lower than NAALS in Maternal Education [E (1,74) = 6.36, p
< .05], Paternal Education [E (1,74) = 11.74, p < .01], Annual Family Income [E
(1,74) = 6.96, p < .05], and Family SES [E (1,74) = 4.62, p < .05]. The only
significant Univariate E for Recovery Status was that fathers in Recovering families
were older than fathers in Non-Recovering families [E ( 1,74) = 4.91, p < .05].
Child Outcome Variables

Intellectual Functioning and Academic Achievement. Table 8 shows analyses
for FTC IQ scores and WRAT-R standard scores. As can be seen in the table, the 2
(Risk Group) X 2 (Recovery Status) ANOVA on FTC IQ scores showed that girls in
AAL families had lower IQs than did girls in NAAL families. The analysis also

revealed that girls in Non-Recovering alcoholic homes had lower IQs than did girls

58

Table 7. Demographic Characteristitcs of AAL and NAAL Families with Girls
Considering Fathers’ RecovergStzlug

 

RISK UKUUI’

KbCUVbKY S 1A1 US

 

AALs NAALS TOTALS
(L1=27) (1.1=51)
RECOVERY

VARIABLE STATUS Mean (SD) Mean (SD) Mean (SD) p
FTC Age Recovering 6.90 (2.52) 7.94 (2.99) 7.55 (2.81) 24
NonRecov. 6.71 (2.37) 5.80 (2.36) 6.10 (2.38) 54

Risk Group Totals 6.78 (2.37) 6.43 (2.72)
Maternal Recovering 33.13 (2.45) 35.80 (4.83) 34.80 (4.24) 24
Age NonRecov. 34.21 (4.31) 34.51 (3.94) 34.41 (4.03) 54

Risk Group Totals 33.85 (3.78) 34.89 (4.21)
Paternal Recovering 39.70 (7.95) 38.39 (6.28) 38.88 (6.81)1 24
Age NonRecov. 36.65 (5.05) 35.24 (4.58) 35.71 (4.74)1 54

Risk Group Totals 37.67 (6.18) 36.17 (5.27)
Maternal Ed. Recovering 12.78 (1.72) 14.27 (2.15) 13.71 (2.10) 24
(in years) NonRecov. 12.67 (1.71) 13.69 (2.03) 13.35 (1.97) 54

Risk Group Totals 12.70 (1.68)“ 13.86 (2.06)3
Paternal Ed. Recovering 12.44 (1.67) 15.00 (2.27) 14.04 (2.39) 24
(in years) NonRecov. 12.50 (1.69) 13.44 (2.09) 13.13 (2.00) 54

Risk Group Totals 12.48 (1.65)" 13.90 (2.24)a
Annual Recovering 35.83(l2.50) 50.67 (14.83) 45.10 (15.56) 24
Family Inc. NonRecov. 28.56(21.82) 41.04 (22.65) 36.88 (22.96) 54

Risk Group Totals 30.98(19.28)’I 43.87 (20.99)"I
Family SES Recovering 30.61 (9.43) 41.59 (16.10) 37.47 (14.77) 24
NonRecov. 29.14(12.50) 33.55 (14.67) 32.08 (14.02) 54

Risk Group Totals

29.63(11.40)al 35.91 (15.39)3

Multivariate E for Risk Group (7,68) = 2.72‘
Multivariate E for Recovery Status (7,68) = 2.60 '
Multivariate E for Risk X Recovery (7,68) = 0.81

 

Note. Annual Family Income is represented in ten thousand dollar units.
Family SES is represented in units of 10.
Matching superscripts represent significant group differences on Univariate Es
with d_f of (1,74). No significant univariate interactions were found.

‘p< .05

59

Table 8. Intellectual and Achievement Results of Girls in AAL and NAAL Families
in Recovering and Non-Recovering Homes

 

 

 

RISK GROUP RECOVERY STATUS
AALs NAALS TOTALS
RECOVERY
VARIABLE STATUS Mean (SD) Mean (SD) Mean (SD) g
(Ll=27) (E=51)
FTC IQ Recovering 0.36 (0.83) 1.03 (0.79) 0.78 (0.86) 24
(z-score) NonRecov. 0.08 (1.06) 0.34 (0.86) 0.26 (0.93) 54
Risk Group Totals 0.17 (0.98) 0.55 (0.89)
(L1=14) (L1=26)
WRAT-R Recovering 95.40 (16.02) 104.50 (18.81) 101.47 (17.90) 15
Reading NonRecov. 97.44 (13.21) 94.56 (14.56) 95.60 (13.88) 25
Risk Group Totals 96.71 (13.69) 98.38 (16.70)
WRAT-R Recovering 99.40 (12.12) 103.20 (15.35) 101.93 (14.03) 15
Spelling NonRecov. 90.44 (17.40) 91.31 (11.57) 91.00 (13.60) 25
Risk Group Totals 93.64 (15.85) 95.88 (14.14)
WRAT-R Recovering 93.20 (7.79) 106.40(17.32) 102.00 (15.86) 15
Arithmetic NonRecov. 88.33 (16.58) 92.63 (15.33) 91.08 (15.59) 25

Risk Group Totals 90.07 (13.92) 97.92 (17.20)

 

AN OVAS and MANOVAS

 

 

 

Variable Multivariate Es Univariate Es
FTC IQ Risk Group (1,74) = 4.15'
Recovery Status (1,74) = 4.46‘
Risk X Recovery (1,74) = 0.80
WRAT-R Risk Group (3,34) = 0.91
Recovery Status (3,34) = 338'
Risk X Recovery (3,34) = 1.05
Reading Recovery Status (1,36) = 0.54
Spelling Recovery Status (1,36) = 4.63'
Arithmetic Recovery Status (1,36) = 3.05
Planned Comparisons
Controls Recovering Fathers Non-Recov. Fm
Variable Mean (SD) Mean (SD) Mean (SD)
FTC IQ 0.80 (0.75)a 0.78 (0.86)b 0.26 (0.93)”
WRAT-R Spelling 102.17 (14.58)al 101.93 (14.03)" 91.00 (13.60)ab

 

Note. All WRAT-R scores are standard scores.
Means with the same superscript on Planned Comparisons differ at p < .05

‘p< .05

60

in families in which alcohol problems continued. There was no significant
interaction between Risk Group and Recovery Status. Finally, a planned comparison
including Control families showed that girls in Non-Recovering alcoholic homes had
lower IQs than did girls in Control families (1 = -3.24, p < .01), but that IQs did
not differ between girls in Control and Recovering families.

A 2 (Risk Group) X 2 (Recovery Status) MANOVA with FTC WRAT-R
scores showed only a significant main effect for Recovery Status. Univariate Es
revealed a significant difference on the Spelling subtest with girls in Non-Recovering
homes scoring lower than girls in Recovering homes. A planned comparison was
performed adding Control families to the analysis. This test showed that girls in
Non-Recovering homes scored lower in Spelling than did Controls (1 = -2.90, p <
.01), but that Spelling scores did not differ between girls in Control and Recovering
families (see Table 8).

Child Behavior Problem_s. Table 9 shows analyses for CBCL Total Behavior
Problems and the two CBCL Broadband factors. As can been seen in the table, the
(Risk Group) X 2 (Recovery Status) ANOVA for Total Behavior Problems showed
that girls in Recovering homes had significantly less problems than girls in Non-
Recovering homes. A planned comparison adding Control girls demonstrated that
these girls in Recovering homes did not differ from Controls, but that girls in Non-
recovering homes had more overall behavior problems than Controls (3 = 3.88, p <
.01). The ANOVA showed no Risk Group main effect, nor a significant interaction.

A 2 (Risk Group) X 2 (Recovery Status) MANOVA for the two CBCL

Broadband factors showed significant effects for Recovery Status only. Univariate Es

61

 

 

 

 

 

 

 

 

Table 9. Parents’ Ratings of Their Daughters’ Behavior Using CBCL Total Behavior
Problems_and Broadband Factors in AAL aknd NAAL Families with Fathers’
Recoveg) Status Considered (T-Scores)
RISK GROUP RECOVERY STATUS
AALs NAALS TOTALS
m=27) (1.1=51)
RECOVERY
VARIABLE STATUS . Mean (SD) Mean (SD) Mean (SD) 3
Total Beh. Recovering 48.39 (5.54) 47.77 (6.36) 48.00 (6.01) 24
Problems NonRecov. 52.61 (7.06) 51.06 (8.09) 51.57 (7.76) 54
Risk Group Totals 51.20 (6.84) 50.09 (7.74)
Extemalizing Recovering 50.28 (5.58) 49.60 (6.31) 49.85 (6.00) 24
Behavior NonRecov. 53.83 (7.35) 52.82 (8.11) 53.16 (7.85) 54
Risk Group Totals 52.65 (6.97) 51.87 (7 .74)
Internalizing Recovering 47.50 (5.36) 47.30 (8.20) 47.37 (7.20) 24
Behavior NonRecov. 50.78 (7.29) 48.89 (8.04) 49.52 (7.81) 54
Risk Group Totals 49.69 (6.84) 48.42 (8.08)
ANOVAS and MANOVAS
Variable Multivariate Es Univariate Es

Total Problems Risk Group (1,152) = 0.68
Recovery Status (1,152) = 8.13"

Risk X Recovery (1,152) = 0.13

 

 

 

 

 

Broadband Risk Group (2,151) = 0.32
Recovery Status (2,151) = 329'
Risk X Recovery (2,151) = 0.22
Extemalizing Recovery Status ( 1,152) = 6.48'
Behavior
Internalizing Recovery Status (1,152) = 3.10
Behavior
flamed Comparison;
Controls Recovering Fathers Non-Recov. Fathers
Variable Mean (SD) Mean (SD) Mean (SD)
Total Problems 47.31 (8.64)‘ 48.00 (6.01)b 51.57 (7 .76)ab
Extemalizing Beh. 48.90 (8.55)a 49.85 (6.00)b 53.16 (7.85)“b

 

Note. Means and Standard Deviations are aggregated across both Parents.

Means with the same superscript on Planned Comparisons differ at p < .05

'p<.05 "p<.01

62

showed that this effect was only significant for Extemalizing Behavior Problems as
girls in Recovering homes had less externalizing behavior than girls in Non-
Recovering homes (see Table 9). Once again, the planned comparison including
Control families showed that girls in Non-Recovering homes had more problems than
Control girls (t = 3.89, p < .01), but that Control girls and Recovering girls did not
differ.

A 2 (Risk Group) X 2 (Recovery Status) MAN OVA for the eight CBCL
Narrowband factors was performed with results shown in Table 10. Only a
significant main effect for Risk Group was found. Univariate Es showed this
significant Risk Group effect only on the Social Problems factor with girls in NAAL
families having less problems than girls in AAL families.

Finally in regards to child behavior problems, no significant differences were
found for a 2 (Risk Group) X 2 (Recovery Status) ANOVA on Teacher TRF Total
Behavior Problems, a 2 (Risk Group) X 2 (Recovery Status) MANOVA on the two
TRF Broadband factors, or a 2 (Risk Group) X (Recovery Status) MANOVA on the

eight TRF Narrowband factors.

63

Table 10. Parents’ Ratings of Their Daughters’ Behavior Using CBCL Narrowband Factors
in AAL and NAAL Families with Fagers’ Recovery Status Considered (T-Scores)

 

RISK UROUI’ KEUUVEKY STA I US

 

 

 

AALs NAALS TOTALS
(E=27) (E=51)
RECOVERY

VARIABLE STATUS Mean (SD) Mean (SD) Mean (SD) 3
Withdrawn Recovering 51.89 (2.65) 53.07 (4.98) 52.62 (4.27) 24
NonRecov. 53.17 (4.32) 54.31 (4.69) 53.93 (4.58) 54

Risk Group Totals 52.74 (3.87) 53.94 (4.78)
Somatic Recovering 53.17 (4.16) 52.00 (3.60) 52.44 (3.82) 24
Complaints NonRecov. 55.42 (5.90) 53.38 (4.46) 54.06 (5.05) 54

Risk Group Totals 54.67 (5.45) 52.97 (4.26)
Anxious/ Recovering 51.39 (2.00) 52.17 (3.65) 51.87 (3.13) 24
Depressed NonRecov. 52.78 (4.54) 52.89 (4.55) 52.85 (4.53) 54

Risk Group Totals 52.31 (3.92) 52.68 (4.30)
Social Recovering 54.11 (5.80) 52.00 (4.23) 52.79 (4.92) 24
Problems NonRecov. 56.31 (7.55) 53.57 (4.83) 54.48 (5.98) 54

Risk Group Totals 55.57 (7.04) 53.11 (4.70)
Thought Recovering 52.17 (3.33) 51.63 (3.74) 51.83 (3.56) 24
Problems NonRecov. 53.14 (5.29) 52.93 (5.32) 53.00 (5.29) 54

Risk Group Totals 52.81 (4.71) 52.55 (4.93)
Attention Recovering 51.83 (2.83) 51.43 (2.22) 51.58 (2.45) 24
Problems NonRecov. 53.83 (4.79) 52.97 (3.68) 53.26 (4.08) 54

Risk Group Totals 53.17 (4.32) 52.52 (3.38)
Delinquent Recovering 53.78 (4.07) 53.63 (5.01) 53.69 (4.64) 24
Behavior NonRecov. 55.78 (6.22) 55.14 (5.43) 55.35 (5.68) 54

Risk Group Totals 55.11 (5.63) 54.70 (5.33)
Aggressive Recovering 52.72 (3.27) 52.33 (3.82) 52.48 (3.59) 24
Behavior NonRecov. 54.97 (5.72) 55.06 (5.71) 55.03 (5.69) 54

Risk Group Totals 54.22 (5.12) 54.25 (5.36)

ANOVAS and MANOVAS

Variable Multivariate Fs Univariate Es

Narrowband Factors

Risk Group (8,145) = 2.28“

Recovery Status (8,145) = 1.53
Risk X Recovery (8,145) = 0.15
Risk Group (1,152) = 5.77'

Social Problems

 

Note.
' p < .05

Means and Standard Deviations are aggregated across both Parents.

Discussion

Research on the etiology of alcoholism has increased substantially in the last
decade. A research design of special interest involves the cohort of children of
alcoholics (COAs) vs. non-COAs. Such designs vary with genetic and contextual
risk because COAs, as a group, appear likely to disproportionately carry risk
characteristics that will lead to later disorders. Thus, by using these designs, one is
able to contrast a higher risk vs. a lower risk population, and explore the potential
contributions of specific attributes to the overall risk equation.

Most recently, some studies have investigated potentially differing effects on
COAs as a function of their parents’ alcoholism subtype (e. g. Ellis et al., 1996;
Zucker et al., 1994a). However, female COAs have been largely ignored in the
earlier work with COAs, as well as the more recent endeavors. The present study
demonstrates that, even at very young ages, there are noticeable differences between
girls reared in alcoholic environments vs. nonalcoholic environments. These
differences are uniformly related to poorer functioning. The study also shows,
however, that such differences are often a function of the subtype of parental
alcoholism, rather than being an overall attribute of familial alcoholism.

Girls in Antisocial Alcoholic (AAL) families had lower levels of intellectual
functioning than did girls in Nonantisocial Alcoholic (NAAL) families, and girls
whose parents do not have alcohol problems. Past research has also demonstrated
lower IQs in COAs (Bennett et al., 1988; Ervin et al., 1984; Gabrielli & Mednick,
1983; Stenhausen et al., 1982), although some studies have not found this effect

(Fitzgerald et al., 1993; Herjanic et al., 1978; Johnson & Rolf, 1988; Tarter et al.,

64

65

1984). Given the substantial evidence for familial alcoholism differences observed
here, the present research suggests that one reason an effect may not have been found
in some of the previous studies was the failure to address the heterogeneity of
parental alcoholism. The present study indicated that only those COAs from AAL
families showed decreased intellectual functioning when compared with non-COAs.
This finding was anticipated, especially given other factors known to
distinguish AAL, from NAAL and Control families. Factors such as paternal and
maternal IQ and education, family SES, and family income have been demonstrated
to differ between groups‘in the current sample, as well as in the larger project
(Bingham, Zucker, & Fitzgerald, 1996; Ellis et al., 1996; Zucker et al., in press).
In addition, AAL families have been shown to have a greater aggregation of other
potential risk factors such as greater amounts and severity of other psychopathology
and family aggression (Ellis et al., 1996). Whether any of these factors have
separate contributions to observed IQ differences (i.e. beyond that indirectly assessed
by grouping families according to risk) remains to be seen in future studies.
Intellectual functioning is also known to have a strong heritable component
(Sattler, 1982). IQ differences have already been observed among men and women
as a function of alcoholic subtype in one previous study (Bingham et al. , 1996). At
the same time, it is likely that other factors found in AAL families may also
negatively influence the cognitive and social stimulation available to the children in
these homes. Such an explanation is consistent with previous research findings that
the quality of stimulation in home environments of alcoholic versus nonalcoholic

homes differed, and thereby impacted the intellectual abilities of very young boys

66
(Noll et al., 1992). It should also be noted that although IQs significantly differed

between AALs and Controls, the AAL girls were still within normal levels thus
reducing the likelihood that the current results were a function of Fetal Alcohol
Syndrome. This potential contribution has already been ruled out as a possible
source of variation among boys (Bingham, Fitzgerald, Fitzgerald, & Zucker, 1996).
The present data are consistent with the null hypothesis for girls, although future
research is needed to test this hypothesis.

Despite the intellectual functioning subtype effect, the current study did not
find significant differences between risk groups, nor interactions with age, in the
academic achievement of the girls. These results are at odds with previous research
findings indicating that COAs show impaired academic functioning relative to non-
COAs (Bennett et al., 1988; Ervin et al., 1984; Hegedus et al., 1984; Marcus,
1986). At the same time, the reader is reminded that the mean age of girls in this
study was less than seven. It may take longer for these effects to become
pronounced enough to be detectable. The other literature in this area is based upon
observations of substantially older children. In addition, it should be remembered
that achievement data were missing on almost half of the girls because many of them
were of preschool age. Thus, achievement findings in the present study need to be
accepted cautiously due to the low statistical power of the analyses.

In terms of behavior problems, the current study shows that female COAs had
greater overall behavior problems, more externalizing behavior, and more social
problems (only AAIs differed from Controls in this area) than did same-aged peers

in nonalcoholic homes. These findings are consistent with past research showing

67

increased levels of behavior problems in COAs (Chassin et al. , 1991; Ellis et al.,
1996; Jacob & Leonard, 1986; Rubio-Stipec et al., 1991). The current study adds to
previous work by showing that these different levels of adaptation are distinguishable
even at very early ages in girls.

The fact that young female COAs showed greater externalizing behavior is an
especially important finding. Lahey and Loeber (1994) have noted that girls have
later onset and less externalizing behavior than boys. However, the current results
indicate that when raised in an alcoholic environment, early vulnerabilities to
aggressive and delinquent behavior are sometimes seen. Longitudinal work is
necessary to see if these relatively small differences (in terms of the absolute
magnitude of problem behavior) between COA and control girls become even greater
as these girls enter into adolescence and young adulthood. Such behavior, combined
with increased alcohol expectancies, has been shown to mediate alcohol involvement
in young adults (Sher et al., 1991).

In the present study, AALs and NAALS did not differ from each other, in
terms of their behavior, except with regard to social problems. It appears that even
at very young ages, AAL girls are more socially immature than NAAL girls and
Controls. This finding, although still within normal limits, provides early evidence
of problems that may exacerbate as the girls get older. Future research is necessary
to elucidate what specific factors of the AAL context lead to these effects.

The fact that girls from AAL families did not show significantly increased
levels of behavior problems in other areas, or in overall behavior problems, does not

replicate the recent findings with boys observed in similar families (Bingham et al.,

68

1996; Ellis et al., 1996). The statistical power in these other studies was greater.
Although it is possible that real effects were masked in the current investigation by
decreased statistical power, it should be noted that the absolute magnitude of the
effects between female COAs and non-COAs observed in the present study were
smaller than the effects seen among boys in the other study (Bingham et al.). Thus,
the increased risk load in AAL families found in the prior studies, may not have the
same impact on young female COAs as it does upon young males.

One explanation for a lack of differences between AAL and NAAL girls is
the fact that the current study’s alcoholic subtyping was based solely on the father’s
level of alcoholism and antisociality. In looking at differential effects on female
COAs, it seems plausible that the risk load of the mothers, and its relationship to
their daughters’ functioning (either separately or in combination with fathers’ risk
load) should also be characterized. Chassin et a1. (1991) found that there was even
greater externalizing behavior in female COAs when the mother in those families was
also alcoholic. As noted in the introductory chapter, there is research indicating that
different alcoholic subtypes also exist among women (e. g., Hill, 1993; Zucker &
Gomberg, 1993). Future studies might try to define alcoholic subtypes in mothers
and use this information in analyses of adaptational differences among female COAs.
Given the special role played by mothers in the socialization of their daughters, it is
plausible that classifying female COAs’ risk based on the mothers’ alcoholism
subtype, would lead to even more refined understanding of COA similarities and
differences.

At the same time, mother differences have indirectly entered into these

69

analyses, given the already demonstrated differences in assortative mating noted
among AALs, NAALS, and Controls (Ellis et al., 1996; Zucker, Ellis, Bingham, &
Fitzgerald, in press). These studies have noted the co-aggregation of father
antisociality differences, with differences in mother psychopathology (e. g. more
antisocial behavior, higher levels of drinking problems, more depression) and social
adaptation (e.g. less education). Thus, the subtype differences reported here,
although based upon a classification of families by way of father functioning,
indirectly were also accessing maternal covariation.

The results of the present study also did not confirm prior findings regarding
greater internalizing behavior in female COAs as compared to control families
(Bingham et al., 1996; Chassin et al., 1991; Ellis et al., 1996; Jacob & Leonard,
1986; Rubio-Stipec et al., 1991). Results from Chassin et al. provided some
indication that maternal alcoholism had a unique effect on children’s internalizing
symptomatology; the lack of specific attention in the current study to the mothers’
risk load variation may again be one reason for the observed lack of effects.

The relatively young ages of the girls may also have contributed to the lack of
differences in internalizing behavior. In the present study, information on child
behavior was obtained through parent report. Parents may have the tendency to
focus more on "acting out" behavior, especially with young female children, as
externalizing behavior is more visible, thus easier to report. For example, lower
scores are needed to fall in the clinical range for Internalizing Behavior Problems
than Extemalizing Behavior Problems on the CBCL, and girls need higher scores

than boys to reach clinical levels for Internalizing Behavior Problems (Achenbach,

70

1991). In addition, the present study found a decrease in the level of Extemalizing
Behavior Problems as a function of age, but not in regard to Total Behavior
Problems or Internalizing Behavior Problems. Thus, the lack of differences between
COA and control girls might be attributable to the age of the girls. The present
study involved only girls in early and middle childhood while the Chassin et al.
(1991) study involved adolescents, the Jacob and Leonard ( 1986) study involved
children ages 10-18, and the Rubio-Stipec et al. (1991) study involved children ages
4-16.

Perhaps the most intriguing finding of the current study was the observation
that the functioning of girls in Recovering Alcoholic families was similar to that of
Control families, and was significantly better than among children currently being
reared in Alcoholic households. These results show that when alcohol problems no
longer exist (at least for the fathers in these families), the girls in these home have
IQs, spelling abilities, levels of total behavior problems, and levels of externalizing
behavior similar to those of girls from families in which alcohol use has never been a
problem. On the other hand, girls in homes where the father continues to have
alcohol problems have lower functioning in all of these areas. These findings are
consistent with results from a follow-up study of children from treatment families
who varied in parental recovery vs. relapse (Moos & Billings, 1982), and a study
using a community-based sample of adolescents from alcoholic families, in which
analyses based on recovery status were done (Chassin et al., 1991). Results from all
three studies indicate that the cessation of alcohol problems leads to the reduction of

the stress-related environment that produces negative outcomes for children. A still

71

unanswered question is whether there is a critical point in the child’s life when the
damage from an alcoholic environment is so severe that the likelihood for improved
child functioning is very low? Longitudinal studies are needed to address such a
question. Another issue requiring further research, concerns the factors that
distinguish those families that recover from alcohol abuse from the ones that don’t.
Factors such as marital issues and social support are obvious candidates for
mechanisms, but there may be others. It is also possible that the same factors that
lead a parent to stop abusing alcohol may mediate or moderate the changes seen in
the children of recovering families, besides contributing to the actual cessation of
parental alcohol problems.
Limitations of tEe Study

Some of the limitations of the current study have already been identified.
First, even though age was considered an important factor to explore, the current
study is cross-sectional in nature. As such, several of the instruments were not
available for all participants (i.e. Health Histories, WRAT-R, and Teacher TRF)
across all time periods. This reduced the number of subjects for analyses in a
sample with already low statistical power. In addition, longitudinal replication of the
current results is necessary, especially with regard to further understanding the
effects of the cessation of alcohol problems in parents.

Second, this study examined the effects of alcohol problems on young girls by
categorizing families based primarily upon fathers’ risk attributes. Although this
methodology has proven useful in studying effects on boys, it appears that the lack of

attention to specific risk factor variation among the mothers may have limited the

72

ability to understand potential effects on girls.

Third, this study examined children’s functioning beginning at a very young
age. As part of a longitudinal study focusing on risk factors and child development,
it is important to document early differences between Alcoholic and Nonalcoholic
families. However, many behavior problems occur at very low base rates among
young children. This makes the task of identifying possible differences even harder.

Fourth, the presence or absence of behavior problems in this study was
assessed only through parent report (teacher reports were obtained but only on a
much smaller subset of the sample). Thus, there is a possibility that the results
obtained, at least in part, reflect parental perception differences between groups,
rather than actual behavior differences among the children. This is especially an
issue since the level of psychopathology differs substantially among the parental
subtype groups. Prior research on the CBCL has shown that this may not be a huge
limitation, as psychologically distressed parents do not rate their children as more
disturbed than normal parents (Conrad & Hammen, 1989), and psychologically
distressed parents rate their children similarly to other independent sources such as
teachers (Richters & Pellegrini, 1989). In addition, the fact that there were group
differences with other observed (rather than perceived) variables in the present study
(i.e. IQ), provides further support that results regarding FTC behavior were not just
a function of parents’ perceptions. Nevertheless, future studies should obtain
information about child functioning from multiple sources.

Finally, although the present research specifically focused on young, female

children because they have been often overlooked, one could argue that the reverse

73

bias was present in this investigation. While it is important to document the effects
of alcoholism on girls, and to identify potential etiologic processes of alcoholism
among women, it may also be useful to directly compare boys with girls. Often, the
ability to comment on gender differences can more easily be done when controlled
for in analyses from the same sample, rather than comparing results from different

samples in different studies.

APPENDICES

APPENDIX A

Drinking and Drug History Questionnaire

74
APPENDIX A

Drinking and Drug History Questionairre

[Zucker, Fitzgerald, & Noll ‘9 1990. Not to be reproduced without the permission of

 

 

 

 

 

the authors]
Information on Drinking and Other Drug Use R Number:
(6/1/89) (13 pages) Given By:
Date:
Tl.0 Ans. Chk:

 

This questionnaire takes about 15 minutes to complete. All information will be used for research only and
will be kept strictly confidential. If you are not sure of the answer to a question please answer the best
you can. Please try to answer each item.

A. THE FOLLOWING QUESTIONS ARE ABOUT YOUR DRINKING OF ALCOHOLIC
BEVERAGES:

1.

HOW OLD WERE YOU THE FIRST TIME YOU EVER TOOK A DRINK? DO NOT
COUNT THE TIMES WHEN YOU WERE GIVEN A "SIP" BY AN ADULT.

 

 

 

 

years old.
2. OVER THE LAST 6 MONTHS, ON THE AVERAGE, HOW MANY DAYS A MONTH
HAVE YOU HAD A DRINK?
days a month.
3. OVER THE LAST 6 MONTHS, ON A DAY WHEN YOU ARE DRINKING, HOW MANY
DRINKS DO YOU USUALLY HAVE IN 24 HOURS? (A DRINK IS A 12 OZ. CAN,
GLASS OR BOTTLE OF BEER; A 4 OZ. GLASS OF WINE; A SINGLE SHOT; OR A
SINGLE "MIXED DRINK")
drinks per 24 hours.
4. OVER THE PAST 6 MONTHS, WHEN YOU GOT DRUNK, HOW BAD WAS YOUR
HANGOVER?
Never bad Pretty Bad
Not bad Terrible
A little less than average Worst possible
Average Never drank enough to get
A little more than average hangover
'OII’V“' ‘0‘ 0'. 3' 'l‘ 3‘ ‘ ‘0 ' “ " ' ‘ '

LAST 6 MONTHS, GO NOW TO PAGE 5, QUESTION 5.

 

ALL OTHERS CONTINUE ON THE NEXT PAGE.
Page 1 of 13

75

B. THE FOLLOWING QUESTIONS ARE ABOUT YOUR DRINKING PATTERNS. IN
ANSWERING THE QUESTIONS, PLEASE THINK ABOUT WHAT YOU HAVE DONE
ON THE AVERAGE OVER THE LAST SIX MONTHS.
1. WHEN DRINKING WINE:

3. HOW OFTEN DO YOU USUALLY HAVE WINE OR A PUNCH CONTAINING WINE?

3 or more times a day 2 or 3 times a month
2 times a day About once a month
Once a day Less than once a month,

Nearly every day but at least once a year

3 or 4 times a week Less than once a year

once or twice a week NEVER [If checked, go to
question #2a]

b. THINK OF ALL THE TIMES YOU HAD WINE OR A PUNCH CONTAINING WINE
RECENTLY. WHEN YOU DRINK WINE, HOW OFTEN DO YOU HAVE 10 OR MORE
GLASSES?

Nearly every time: SKIP TO QUESTION #2 BELOW

More than half the time: SKIP TO QUESTION #2 BELOW
Less than half the time

Once in a while

NEVER

 

C. WHEN YOU DRINK WINE, HOW OFTEN DO YOU HAVE AS MANY AS 7 TO 9
GLASSES?

Nearly every time: SKIP TO QUESTION #2 BELOW

More than half the time: SKIP TO QUESTION #2 BELOW
Less than half the time

Once in a while

NEVER

d. WHEN YOU DRINK WINE, HOW OFTEN DO YOU HAVE AS MANY AS 5 TO 6
GLASSES?

Nearly every time: SKIP TO QUESTION #2 BELOW

More than half the time: SKIP TO QUESTION #2 BELOW
Less than half the time

Once in a while

NEVER

 

e. WHEN YOU DRINK WINE, HOW OFTEN DO YOU HAVE AS MANY AS 3 to 4 GLASSES?

Nearly every time: SKIP TO QUESTION #2 BELOW

More than half the time: SKIP T O QUESTION #2 BELOW
Less than half the time

Once in a while

NEVER

HHI

20f13

76

WHEN YOU DRINK WINE, HOW OFTEN DO YOU HAVE 1 TO 2 GLASSES?

Nearly every time
More than half the time
Less than half the time
Once in a while
NEVER

2. WHEN DRINKING BEER

HOW OFTEN DO YOU USUALLY HAVE BEER?

3 or more times a day 2 or 3 times a month
2 times a day About once a month
Once a day Less than once a month,but at least once
Nearly every day a year
3 or 4 times a week Less than once a year
Once or twice a week NEVER [If checked, go to
question #3a]

THINK OF ALL THE TIMES YOU HAD BEER RECENTLY. WHEN YOU DRINK
BEER, HOW OFTEN DO YOU HAVE 10 OR MORE CANS, GLASSES OR BOTTLES?

Nearly every time: SKIP TO QUESTION #3 BELOW

More than half the time: SKIP TO QUESTION #3 BELOW
Less than half the time

Once in a while

NEVER

WHEN YOU DRINK BEER, HOW OFTEN DO YOU HAVE AS MANY AS 7 TO 9
CANS, GLASSES OR BOTTLES?

Nearly every time: SKIP TO QUESTION #3 BELOW

More than half the time: SKIP TO QUESTION #3 BELOW
Less than half the time

Once in a while

NEVER

WHEN YOU DRINK BEER, HOW OFTEN DO YOU HAVE AS MANY AS 5 TO 6
CANS, GLASSES OR BOTTLES?

Nearly every time: SKIP TO QUESTION #3 BELOW

More than half the time: SKIP TO QUESTION #3 BELOW
Less than half the time

Once in a while

NEVER

30f13

9

” lllll

If!!!

77

WHEN YOU DRINK BEER, HOW OFTEN DO YOU HAVE AS MANY AS 3 to 4 CANS,
GLASSES OR BOTTLES?

Nearly every time: SKIP TO QUESTION #3 BELOW

More than half the time: SKIP TO QUESTION #3 BELOW
Less than half the time

Once in a while

NEVER

WHEN YOU DRINK BEER, HOW OFTEN DO YOU HAVE 1 TO 2 CANS, GLASSES
OR BOTTLES?

Nearly every time
More than half the time
Less than half the time
Once in a while
NEVER

3. WHEN DRINKING WHIS_KEY OR LIQUOR
HOW OFTEN DO YOU USUALLY HAVE WHISKEY OR LIQUOR (SUCH AS

MARTINIS, MANHATTANS, HIGHBALLS, OR STRAIGHT DRINKS INCLUDING
SCOTCH, BOURBON, GIN, VODKA, RUM, ETC.)?

3 or more times a day 2 or 3 times a month

2 times a day About once a month

Once a day Less than once a month, but at least once
Nearly every day a year

3 or 4 times a week Less than once a year

Once or twice a week NEVER [If checked, go to question #4]

THINK OF ALL THE TIMES YOU HAD DRINKS CONTAINING WHISKEY OR OTHER
LIQUOR RECENTLY. WHEN YOU HAVE HAD THEM, HOW OFTEN DO YOU HAVE
10 OR MORE DRINKS?

Nearly every time: SKIP TO QUESTION #4 BELOW

More than half the time: SKIP TO QUESTION #4 BELOW
Less than half the time

Once in a while

NEVER

WHEN YOU HAVE HAD DRINKS CONTAINING WHISKEY OR OTHER LIQUOR,
HOW OFTEN DO YOU HAVE AS MANY AS 7 TO 9 DRINKS?

Nearly every time: SKIP TO QUESTION #4 BELOW

More than half the time: SKIP TO QUESTION #4 BELOW
Less than half the time

Once in a while

NEVER

4OF13

P:

78

WHEN YOU HAVE HAD DRINKS CONTAINING WHISKEY OR OTHER LIQUOR,
HOW OFTEN DO YOU HAVE AS MANY AS 5 TO 6 DRINKS?

Nearly every time: SKIP TO QUESTION #4 BELOW

More than half the time: SKIP TO QUESTION #4 BELOW
Less than half the time

Once in a while

NEVER

WHEN YOU HAVE HAD DRINKS CONTAINING WHISKEY OR LIQUOR, HOW
OFTEN DO YOU HAVE 3 TO 4 DRINKS?

Nearly every time: SKIP TO QUESTION #4 BELOW

More than half the time: SKIP TO QUESTION #4 BELOW
Less than half the time

Once in a while

NEVER

WHEN YOU HAVE HAD DRINKS CONTAINING WHISKEY OR LIQUOR, HOW
OFTEN DO YOU HAVE 1 TO 2 DRINKS?

Nearly every time
More than half the time
Less than half the time
Once in a while
NEVER

4. WHEN DRINKING ANYTHING, CHECK HOW OFTEN YOU HAVE ANY

DRINK CONTAINING ALCOHOL, WHETHER IT IS WINE, BEER, WHISKEY
OR ANY OTHER DRINK. MAKE SURE THAT YOUR ANSWER IS NOT LESS
FREQUENT THAN THE FREQUENCY REPORTED ON ANY OF THE
PRECEDING QUESTIONS.

3 or more times a day Once or twice a week

2 times a day 2 or 3 times a month

Once a day About once a month

Nearly every day Less than once a month, but at least once
3 or 4 times a week a year

Less than once a year

 

5. Now a question about earlier in your life: HOW OLD WERE YOU THE FIRST TIME
YOU EVER DRANK ENOUGH TO GET DRUNK?

years old.

79

63. WE ARE ALSO INTERESTED IN THE OCCASIONS THAT MAY BE RARE (OR
NOT), WHEN PEOPLE DRINK A LOT MORE THAN THEY USUALLY DO. IN
THE LAST SIX MONTHS, THINK OF THE 24 HOUR PERIOD WHEN YOU DID
THE MOST DRINKING; THIS WOULD BE A DAY SOMEWHERE IN THE
PERIOD BETWEEN AND NOW.

(month) (year)

On that day, how many drinks did you have? (A drink is a 12 oz. can, bottle, or glass
of beer, a 4 oz. glass of wine, a single shot, or a single mixed drink).

30 or more drinks
25 - 29 drinks

20 - 24 drinks

15 - 19 drinks

10 - l4 drinks

7 - 9 drinks

5 - 6 drinks

3 - 4 drinks

1 - 2 drinks
none

6b. APPROXIMATELY WHEN DID THIS HAPPEN?

9

(month) (year)

60. NOW ANSWER THIS QUESTION FOR ANY TIME IN YOUR LIFE BEFORE
THESE LAST SIX MONTHS. IN THE 24 HOUR PERIOD WHEN YOU DID THE
MOST DRINKING, HOW MANY DRINKS DID YOU HAVE?

30 or more drinks
25 - 29 drinks

20 - 24 drinks

15 - 19 drinks

10 - l4 drinks

7 - 9 drinks

5 - 6 drinks

3 - 4 drinks

1 - 2 drinks
none

6d. APPROXIMATELY WHEN DID THIS HAPPEN?

9

(month) (year)

6of13

80

ANSWER KEY FOR QUESTIONS BELOW:
1 2 3-5 6-10 11-20 21-50 51-100

101-250 251-500 501-1000 1000+ (more than 1000)

C. NOW SOME QUESTIONS ABOUT OUTCOMES PEOPLE SOMETIMES HAVE BECAUSE OF
DRINKING. HAVE YOU EVER HAD ANY OF THE FOLLOWING HAPPEN BECAUSE OF
YOUR DRINKING?

HOW MANY AGE AGE
fl N_O TIMES first most
(check one) (approx.- time recent

see key)* time

1. Missed school or time on job

2. Thought I was drinking too
much

 

 

3. Gone on a binge of constant
drinking for 2 or more days

4. Lost friends

 

 

5. My spouse or others in my
family (my parents or children)
objected to my drinking

 

6. Felt guilty about my drinking

 

7. Divorce or separation

8. Took a drink or two first
thing in morning

 

 

9. Restricted my drinking to
certain times of day or week
in order to control it
or cut down, (like after 5PM,
or only on weekends,
or only with other people)

10. Been fired or laid off

11. Once started drinking,
kept on going till
completely intoxicated

 

 

 

12. Had a car accident when I
was driving

* SELECT YOUR ANSWER FROM KEY AT THE TOP OF THE PAGE

 

Questions continue on the next page.
7 of 13

13.

14.

15.

16.

l7.

l8.

19.

20.

21.

22.

81

ANSWE_R KEY FOR QUESTIONS BELOW:

1 2 3-5 6-10 11-20 21-50 51-100
101-250 251-500 501-1000 1000+ (more than 1000)
HOW MANY AGE AGE
YES N_O TIMES first most
(check one) (approx.- time recent

see key)*

Kept on drinking after

 

I promised myself not to

Had to go to a hospital

 

(other than accidents)

Had to stay in a hospital

 

overnight

Had the shakes "the

 

morning after"

Heard or saw or felt things

 

that weren’t there,
hallucinations) several
days after stopping drinking

Had blackouts (couldn’t

 

remember later what
you’d done while drinking)

Been given a ticket for

 

drunk driving (DWI or DUIL)
Had a jerking or fits

 

(convulsions) several days
after stopping drinking

Been given a ticket for

 

public intoxication, drunk
and disorderly, or other
nondriving alcohol arrest

Had the D.T.’s (delirium

 

tremens, shakes, sweating,
rapid heart, etc.)

within 2 - 3 days

after stopping drinking

* SELECT ANSWERS FROM THE KEY AT THE TOP OF THE PAGE

80f13

time

82

D. THE LAST SECTIONS OF THIS QUESTIONNAIRE DEAL WITH VARIOUS DRUGS OTHER
THAN ALCOHOL. THERE IS STILL A LOT OF TALK THESE DAYS ABOUT THIS SUBJECT,
BUT VERY LITTLE ACCURATE INFORMATION, PARTICULARLY ABOUT PATTERNS OF USE
OF THESE SUBSTANCES IN ADULTHOOD. THEREFORE, WE STILL HAVE A LOT TO LEARN
ABOUT THE ACTUAL EXPERIENCES OF PEOPLE YOUR AGE.

WE HOPE THAT YOU CAN ANSWER ALL QUESTIONS; BUT IF YOU FIND ONE WHICH
YOU FEEL YOU CANNOT ANSWER HON ESTLY, WE WOULD PREFER THAT YOU LEAVE IT
BLANK.

REMEMBER THAT YOUR ANSWERS WILL BE KEPT STRICTLY CONFIDENTIAL AND
THEY ARE NEVER CONNECTED WITH YOUR NAME. THAT IS WHY THIS QUESTIONNAIRE
IS IDENTIFIED ONLY WITH A CODE NUMBER.

THE FOLLOWING QUESTIONS ARE ABOUT CIGARETTES (CHECK THE BEST ANSWER):

1a. HAVE YOU EVER SMOKED CIGARETTES?

Never (GO TO QUESTION 3)
Once or twice

Occasionally but not regularly
Regularly in the past
Regularly now

lb. HAVE YOU SMOKED CIGARETTES DURING THE PAST 12 MONTHS?

Never (GO TO QUESTION 3)

Once or twice

Occasionally but not regularly

Regularly for a while during this year, but not now
Regularly now

Not at all

Less than one cigarette per day

One to five cigarettes per day

About one-half pack per day

About one pack per day

About one and one-half packs per day
Two packs or more per day

E. THE FOLLOWING QUESTIONS ARE ALL ABOUT NON-PRESCRIPTION USE OF DRUGS,
EITHER FOR RECREATION OR FOR SELF-MEDICATION.

(MARK ONE SPACE FOR EACH LINE).

3.

ON HOW MANY OCCASIONS (IF ANY)

HAVE YOU USED MARUUANA

(GRASS, POT) OR HASHISH

(HASH, HASH OIL)

9 10—19 20-39 40-99 100-1000 > 1000
) ( ) ( ) ( ) ( ) ( )
) ( ) ( ) ( ) ( ) ( )

0
In your lifetime? (
During the last (
12 months?
Duringthelast30days? () () () () () () () () ()
9 of 13

)
)

83

(MARK ONE SPACE FOR EACH LINE).
4

ON HOW MANY OCCASIONS
(IF ANY) HAVE YOU USED
LSD (ACID) 0 1-2 3-5

In your lifetime? (

During the last (
12 months?

During the last 30 days? ( ) ( ) ( )

5.

ON HOW MANY OCCASIONS

(IF ANY) HAVE YOU USED

PSYCHEDELICS OTHER THAN

LSD (LIKE MESCALINE,

PEYOTE, PSILOCYBIN, PCP)

)
) () ()

In your lifetime? (

During the last (
12 months?

During the last 30 days? ( ) ( ) ( )

6.

ON HOW MANY OCCASIONS

(IF ANY)

HAVE YOU USED COCAINE

(COKE OR CRACK)

)
) () ()

() ()

In your lifetime? (
( ( ) ( )

During the past
12 months?
During the last 30 days? ( ) ( ) ( )

7.

AMPHETAMINES ARE SOMETIMES
PRESCRIBED BY DOCTORS TO
HELP PEOPLE LOSE WEIGHT OR
TO GIVE PEOPLE MORE ENERGY.
THEY ARE SOMETIMES CALLED
UPPERS, UPS, SPEED, CRYSTAL,
CRANK, BENNIES, DEXIES, PEP
PILLS, AND DIET PILLS.

)
)

ON HOW MANY OCCASIONS (IF ANY)
HAVE YOU TAKEN AMPHETAMINES ON
YOUR OWN--THAT IS, WITHOUT A
DOCTOR TELLING YOU

TO TAKE THEM

In your lifetime? ( )

During the last ( )
12 months?

During the last 30 days? ( ) ( ) ( )

(
(

AA
vv

)
)

6-9 10-19

() (
() (

() (

() (
() (

() ()

10 of 13

)
)

)

)
)

20-39 40-99 100-1000 >1000

(
(

AA
AA
vv

Vv
AA
VV

)
)
() () () ()

(MARK ONE SPACE FOR EACH LINE).

4.

ON HOW MANY OCCASIONS
(IF ANY) HAVE YOU USED
LSD (ACID) 0

In your lifetime? ( )

During the last ( )
12 months?

During the last 30 days? ( )

5.

ON HOW MANY OCCASIONS

(IF ANY) HAVE YOU USED

PSYCHEDELICS OTHER THAN

LSD (LIKE MESCALINE,

PEYOTE, PSILOCYBIN, PCP)

In your lifetime? (

During the last (
12 months?

During the last 30 days? ( )

6.

ON HOW MANY OCCASIONS

(IF ANY)

HAVE YOU USED COCAINE

(COKE OR CRACK)

)
)

In your lifetime? (

During the past (
12 months?

During the last 30 days? ( )

7

)
)

()
()

()

AMPHETAMINES ARE SOMETIMES

PRESCRIBED BY DOCTORS TO
HELP PEOPLE LOSE WEIGHT OR

TO GIVE PEOPLE MORE ENERGY.

THEY ARE SOMETIMES CALLED
UPPERS, UPS, SPEED, CRYSTAL,
CRANK, BENNIES, DEXIES, PEP

PILLS, AND DIET PILLS.

ON HOW MANY OCCASIONS (IF ANY)

HAVE YOU TAKEN AMPHETAMINES ON
YOUR OWN--THAT IS, WITHOUT A

DOCTOR TELLING YOU
TO TAKE THEM

In your lifetime? ( )

During the last ( )
12 months?

During the last 30 days? ( )

(
(

()

)
)

AA
VV

()

6-9 10-19 20-39 40-99100-1000 >1000

)
)

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vv
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() () () (
() () () (
() () () () () ()
100f13

84

(MARK ONE SPACE FOR EACH LINE).

8 0

1-2 3-5 6-9 10-19

ON HOW MANY OCCASIONS (IF ANY)

HAVE YOU USED QUAALUDES

(QUADS, SOAPERS, METHAQUALONE)
ON YOUR OWN» THAT IS, WITHOUT

A DOCTOR TELLING
YOU TO TAKE THEM

In your lifetime? (
During the last (
12 months?

During the last 30 days? ( )

9

) )
) )

AA
AA
vv

( (
( (

() () () ()

BARBITURATES ARE SOMETIMES PRE-
SCRIBED BY DOCTORS TO HELP PEOPLE
RELAX OR GET TO SLEEP. THEY ARE
SOMETIMES CALLED DOWNS, DOWNERS,
GOOFBALLS, YELLOWS, REDS, BLUES,

RAIN BOWS.

ON HOW MANY OCCASIONS
(IF ANY) HAVE YOU TAKEN

BARBITURATES ON YOUR OWN --

THAT IS, WITHOUT A DOCTOR
TELLING YOU TO TAKE THEM

In your lifetime? ( )
( )

During the last
12 months?

During the last 30 days? ( )

10.

() () )
() () )

AA
vv

(
(
() () () ()

TRANQUILIZERS ARE SOMETIMES
PRESCRIBED BY DOCTORS TO CALM
PEOPLE DOWN, QUIET THEIR NERVES,
OR RELAX THEIR MUSCLES. LIBRIUM
VALIUM, AND MILTOWN ARE ALL

TRANQUILIZERS.

ON HOW MANY OCCASIONS (IF ANY)
HAVE YOU TAKEN TRANQUILIZERS

ON YOUR OWN -- THAT IS,

WITHOUT A DOCTOR TELLING YOU

TO TAKE THEM

In your lifetime? (
During the last (
12 months?

During the last 30 days? ( )

AA
vv
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() () () ()

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20-39 40-99 100-1000 >1000

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( )

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( )

AA
VV
AA
vv

() ()

AA
vv
AA

AA
vv
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VV

() ()

(MARK ONE SPACE FOR EACH LINE).

11.
ON HOW MANY OCCASIONS (IF ANY)
HAVE YOU USED HEROIN (SMACK,
HORSE, SKAG)

0 1-2 3-5
In your lifetime? (
During the last (

12 months?

During the last 30 days? ( ) ( ) ( )

)
) () ()

12.

THERE ARE A NUMBER OF NARCOTICS
OTHER THAN HEROIN, SUCH AS METH-
ADONE, OPIUM, MORPHINE, CODEINE,
DEMEROL, PAREGORIC, TALWIN, AND
LAUDANUM. THESE ARE SOMETIMES
PRESCRIBED BY DOCTORS.

ON HOW MANY OCCASIONS (IF ANY)
HAVE YOU TAKEN NARCOTICS OTHER
THAN HEROIN ON YOUR OWN--

THAT IS, WITHOUT A DOCTOR
TELLING YOU TO TAKE THEM

In your lifetime? ( ) (

During the last ( ) (
12 months?

During the last 30 days? ( ) ( ) ( )

) ()
) ()

13.

ON HOW MANY OCCASIONS (IF ANY)
HAVE YOU SNIFFED GLUE, OR
BREATHED THE CONTENTS OF
AEROSOL SPRAY CANS, OR INHALED
ANY OTHER GASES OR SPRAYS IN
ORDER TO GET HIGH

In your lifetime? (

During the last (
12 months?

During the last 30 days? ( ) ( ) ( )

)
)

AA
vv

) (
) (

6-9 10-19
( ) ( )
( ) ( )

() ()

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20-39 40-99 100-1000 >1000

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86

F. NOW SOME OTHER QUESTIONS ABOUT NONPRESCRIPTION USE OF DRUGS. HAVE
YOU EVER HAD ANY OF THE FOLLOWING OUTCOMES BECAUSE OF YOUR USE OF
THE NONPRESCRIPTION DRUGS ASKED ABOUT IN SECTION B (THE LAST
SECTION)?

ANSWER KEY FOR QUESTIONS BE_LOW:

l 2 3-5 6-10 11-20 21-50 51-100 101-250 251-500 500+
YES IQ HOW MANY AGE AGE
TIMES first most recent
(approx) TIME TIME
(see key)*

1. Missed school or time on job
. Lost friends

. Been divorced or separated

. Been fired or laid off

. Had a car accident when
you were driving

LIIJKUJN

6. Had to go to a hospital
(other than accidents)

7. Had to stay in hospital
overnight

8. Had to see a doctor because
of drug use (unintentional
overdose) or had a doctor
say drugs had harmed your health

9. Gone through physical with-
drawal from drugs

10. Been arrested for
possession or sale
of drugs other than marijuana

* SELECT YOUR ANSWER FROM KEY AT THE TOP OF THE PAGE

11a. Have you ever taken drugs intravenously (using a needle)? Don’t count shots you were given
by a doctor or nurse or shots you may have taken for treatment of diabetes.

NO YES

 

llb. IF YES, WHAT DRUGS HAVE YOU TAKEN INTRAVENOUSLY (IV)?

 

11c. AT WHAT AGE DID YOU FIRST TAKE AN 1V DRUG? years old.
11d. AT WHAT AGE WAS THE MOST RECENT TIME? years old.
13 of 13

 

 

APPENDIX B

Antisocial Behavior Inventory

87
APPENDIX B

Antisocial Behavior Inventory
[Zucker & Noll © 1980. Not to be reproduced without the permission of the authors]

Many of us have had adventures during our lives...times that were exciting and carefree,
even though they may have been a bit impulsive or happy-go-lucky. Please read each of the
following items. Indicate (with a check) if you have ever done any of the following activities
and how often.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

NEVER - You have never done this
RARELY - Once or twice in your life
SOMETIMES - Three (3) to nine (9) times in your life
OFTEN - More than ten (10) times in your life
N R S O
E A O F
V R M T
E E E E
R L T N
Y I
M
E
S
E E E E 1. Skipped school without a legitimate excuse for more than 5 days in one
I I I I
l I l I school year.
E E E E 2. Been suspended or expelled from school for fighting.
E E E E 3. Been suspended or expelled from school for reasons other than fighting.
E E E E 4. Lied to a teacher or principal.
E E E E 5. Cursed at a teacher or principal (to their face).
E E E E 6. Hit a teacher or principal.
I l T l .
E :L E E 7. Repeated a grade in school.
E E E E 8. Taken part in a gang fight.
E E E E 9. "Beaten up" another person.
E E E E 10. Broken street lights, car windows, or car antennas
! i E E just for the fun of it.

 

Page 1 of3

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ZlTI—I’TIO

NEVER
RARELY -
SOMETIMES
OFTEN

88

You have never done this

Once or twice in your life

Three (3) to nine (9) times in your life

More than ten (10) times in your life

 

 

 

 

 

11.

Gone for a ride in a car someone else stole.

 

12.

Teased or killed an animal (like a dog or cat) just for the fun of it.

 

l3.

Defied your parent’s authority (to their face).

 

14.

Hit your parents.

 

15.

Cursed at your parents (to their face).

 

16.

Stayed out overnight without your parent’s permission.

 

17.

Run away from home for more than 24 hours.

 

18.

Lied to your parents.

 

19.

20.

Snatched a woman’s purse.

Rolled drunks just for the fun of it.

 

21.

Shoplifted merchandise valued over $25.

 

22

Shoplifted merchandise valued under $25.

 

23.

Received a speeding ticket.

 

. Been questioned by the police.

 

. Taken part in a robbery.

 

Taken part in a robbery involving physical force or a weapon.

 

L-.--u---—.L--qb-----qh--p—-_-q---—--—d--d--q--

p—--—-d-—-q--d--q--q--q--db-—fin----q--.----q----——-

L-J--d-——+-——dh-d--I———dh—-up-D-——-u——--—up-—dP-q—-.--qp-

. Been arrested for a felony.

 

Page 2 of 3

89

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

41.

Lied to your spouse.

 

42.

Spent six months without any job or permanent home.

 

43.

Been fired for excessive absenteeism.

 

. Been fired for poor job performance (except absenteeism).

 

45.

Changed jobs more than 3 times in one year.

 

E-—-1I-—---II--II--I-—-
t

46.

N R S O
E A O F
V R M T
E E E E NEVER ~ You have never done this
R L T N RARELY - Once or twice in your life
Y I SOMETIMES - Three (3) to nine (9) times in your life
M OFTEN - More than ten (10) times in your life
E
S
E E E E 28. Resisted arrest.
E E E E
E E E E 29. Been arrested for any other non-traffic police offenses
E E i E (except fighting or a felony).
E E E E 30. Been convicted of any non-traffic police offense.
E E E E 31. Defaulted on a debt.
E E E E 32. Passed bad checks for the fun of it.
E E E E 33. Ever used an alias.
E E E E
E E E E 34. Gone AWOL from the military.
E E E E 35. Received a bad conduct or undesirable discharge from the military.
E E E E 36. Performed sexual acts for money.
E E E E 37. Engaged in homsexual acts.
I I I I
E E E E 38. Had intercourse with more than one person in a single day.
I l 1 l
E E E E 39. "Fooled around" with other women/men after you were married.
E E E E 40. Hit your husband/wife during an argument.
I : : w
I I I
E E E
I I I
l I I
l J I
I I V
I I I
E E E
I I I
l I I
E E E
I I I
I I I
I l l
I I T
l E I

Lied to your boss.

 

Thafik you very mat for your cooperation.
Page 3 of 3

APPENDIX C

Child Health and Developmental History

90
APPENDIX C

Child Health and Development History

[Zucker & Fitzgerald © 1992. Not to be reproduced without the permission of the
authors]

MICHIGAN STATE UNIVERSITY FAMILY STUDY

 

CHILD HEALTH AND DEVELOPMENT HISTORY
(4/92)

RESPONDENT NUMBER: _____
TARGET: _ __ _
GIVEN BY:
DATE: _/__/

T2.0 T3.0 T4.0

91

I. BACKGROUND INFORMATION
Target Child’s First Name: [ ]

Q1. Child date of birth: _/_/

Q2. Child age: Years, Months

Q3. School Name: School Grade:
Instructions: Please answer each question by circling the corresponding number, and
filling in the appropriate information. When the question asks for age when
an event occurred, write in the age of the child in years, and months. (i.e. 12
year, 2 months)

 

II. SERVICES, PROGRAMS
The next set of questions are concerning whether your child has ever been enrolled in
any special program at school or received any special help.
QlA. Has [ I ever been in counseling?
(Child psychiatrist, pediatrician, psychologist, social worker, school
psychologist/counselor, minister, others [specijy])

 

 

 

 

 

1 ................ YES
2 ................ NO [GOTO QlB]
Whom:
Age Started: . to Age:
Year Month Year Month

 

 

QlB. Has [ I ever been tutored?
(Teacher, other adult tutor, peer tutor, others [specijy])

 

 

 

 

 

1 ................ YES
2 ................ NO [GOTO Q1C]
Whom:
Age Started: . to Age:
Year Month Year Month

 

 

QIC. Has [ I ever had speech therapy?
(Speech therapist, occupational therapist, other [specifiy])

 

 

 

 

1 ................ YES
2 ................ NO [GOTO QlD]
Whom:
Age Started: to Age:
Year Month Year Month

 

 

 

92
QlD. Has [ I ever had reading help?

(Special education teacher, regular teacher, learning center stafi”, other [specijyfl

 

 

 

 

 

1 ................ YES
2 ................. NO [GOTO QlE]
'Whorn: . I
7 Age Started: , . A a ,to Age: ,.
' ~ 4 ' ' .YearMonth .» ; YearMonth-

 

 

QlE. Has [ I ever had any other type of help?

 

 

 

 

 

 

1 ................ YES
2 ................. NO [GOTO III, Q1]
Service: A C V .
'IWhom:
Age Startedzg ' i . " to Age: _ H T ' f
' }.Year.Month   . w. {Yea Month

 

 

 

III. OTHER INFORMATION

Q1. Does [ I have a regular physician or a clinic he/she usually

attends?
1 ................ YES

 

2 ................. NO [GOTO Q2]

 

 

Physician’s NM or Clinic 's Ngme . .

 

 

Q2. Do you remember the date of [ I’s last physical examination?

 

 

1 ................ YES
2 ................. NO [GOTO Q3]
(M th , . ear, as h .si l)

 

 

 

 

Q3. What is [ I’s current height?

ft. ins.

Q4. What is [ I’s current weight?

lbs.

93

IV. CHILD’S HEALTH
Q1. Has [ I ever been on a medication program for hyperactivity for a
period of time, such as ritalin or other medication?

 

l ................ YES
2 ................. NO [GOTO Q2]
AGESTARTED: *  , ° 'TOAGE: ,  . ,
‘ I. (Year, month) 7 ‘ _ (Year, month) _ f  

 

 

 

Q2. Has [ I ever been on a medication program for any other long term or
chronic condition?

 

 

 

 

 

 

 

l ................ YES
2 ................ NO [GOTO Q33]
* MEDICATION AGE STARTEDITOAGE’ _: REASON (CONDITION). 9 "
' :(Year,’month) * . (Year, month) ' ' ' V ’9 *
1. I 9 V ?

 

 

 

The next set of questions deal with other medications [ I has taken in the past 12
months. If he/she has taken the medication, write in the brand of medication taken, TOTAL
number of days he/she has taken the medication in the past 12 months, and the reason(s) for
taking them. Use the following answer key for the number of days for questions Q3a

through Q31:

 

  ,6-1‘0" 11-20 - 21-50 51400 ' 101+" 201—
days - days days, . V days 200 . . 365 p
‘ - i '-~% adaysi" days,

 

 

 

 

 

 

 

 

 

Q3a. Has [ I taken any pain or fever relievers (aspirin, Tylenol, etc.) in the past 12

months?
1 ........................ YES
2 ......................... NO [GOTO Q3b]

 

 

 

 

f ,MEDICATION DAYS REASON (ILLNESS/CONDITION) .

 

 

Q3b. Has [ Itaken any cough medicine (Robitussin, Pediacare, Triaminic, etc.) in the
past 12 months?

1 .................. YES
2 ................... NO [GOTO Q3c]

 

 

 

 

MEDICATION DA rs REASON (ILLNESS/CONDITION)

 

 

Q3c.

Q3d.

Q3c.

Q3f.

Q3g.

94

Has [ Itaken any decongestants/nasal spray (Sudafed, Dimetapp, Actifed, etc.) in
the past 12 months?

1 .................. YES
2 ................... NO [GOTO Q3d]

 

 

 

 

MEDICATION DAYS v REASON (ILLNESS/CONDITION) ; . 1.

 

Has [ I taken any Antihistamines (Chlortrimaton, Acttfed, Benadryl, etc.) in the past
12 months?

1 .................. YES
2 ................... NO [GOTO Q36]

 

 

 

 

MEDICATION DA Ys REASON (ILLNESS/CONDITION); .3. .

Has [ I taken any multisympton cold remedies (Nyquil, Corididin, Cotylenol, etc.)
in the past 12 months?

 

1 .................. YES
2 ................... N O [GOTO Q3f]

 

 

 

 

; MEDICATION DAYS * REASON (ILLNESS/CONDITION) * . ’
Has I I taken any antibiotics (Penicillin, Amoxicillin, etc.) in the past 12 months?

 

1 .................. YES
2 ................... NO [GOTO Q3 g]

 

 

 

 

I ‘MEDICATION DAYS REASON (ILLNESS/CONDITION)

 

Has [ I taken any asthma medication in the past 12 months?

1 .................. YES
2 ................... N O [GOTO Q3b]

 

 

 

 

‘MEDICATION TDAYS REASON (ILLNESS/CONDITION), ,

 

Q3h.

Q3i.

Q31 -

Q3k.

Q31.

95
Has I I taken any allergy medication in the past 12 months?

1 .................. YES
2 ................... N O [GOTO Q3 i]

 

 

 

"MEDICATION DAYS REASON (ILLNESS/CONDITION)

 

 

Has [ I taken any vitamins/dietary supplements in the past 12 months?

1 .................. YES
2 ................... N O [GOTO Q3j]

 

 

 

w MEDICATION. DA is REASON (ILLNESS/CONDITION) . "

 

 

Has [ I taken any laxatives/enemas in the past 12 months?

1 .................. YES
2 ................... NO [GOTO Q3k]

 

 

 

» MEDICATION DAYS REASON (ILLNESS/CONDITION) :

 

 

Has [ I taken any antacids (PeptoBismol, Milk of Magnesia, etc.) past 12 months?

1 .................. YES
2 ................... NO [GOTO Q31]

 

 

 

MEDICATION DAYS ,REASONULLNESS/CONDITION)

 

 

Has [ I taken any other medications in the past 12 months?

1 .................. YES
2 .................... NO [GOTO Q4]

 

 

 

' MEDICATION DA is REASON (ILLNESS/CONDITION)

 

 

96

Q4. Has [ I ever been hospitalized?

 

1 .................. YES
2 .................... NO [GOTO Q5]
AGE IN.. REASON: OPERATION OR ILLNESS # OF DAYS

(years, months)

 

 

 

 

 

 

 

Q5. Has [ I ever been in any accidents resulting in injury serious enough to require
immediate medical treatment (e.g., broken bones, concussion, stitches, burns,
poisonings/accidental ingestion, etc. )?

 

l .................. YES
2 .................... NO [GOTO Q6]
AGE IN.. REASON: INJURY OR ACCIDENT # OF DAYS

(years, months)

 

 

 

 

 

 

 

Q6. What is the highest fever [ I has had?

 

 

TEMPERATURE: AGE: , .
, (years. months) _ .

 

 

 

 

97

Q7. This question deals with possible diseases/ailments [ I has had, or currently has.
Please circle all the diseases/ailments [ I has ever had.
(Circle All That Apply)

a. ASTHMA ..................... l
b. MEASLES ..................... 1
c. MENINGITIS ................... 1
d. GERMAN MEASLES (RUBELLA) ..... 1
e. PNEUMONIA .................. 1
f. HEART MURMUR ............... 1
g. MUMPS ...................... 1
h. ENCEPHALITIS ................. 1
i. SCARLET FEVER ................ 1
j. RHEUMATIC FEVER ............. 1
k. SEIZURES ..................... 1
1. CHICKEN POX ................. 1
m. MONONUCLEOSIS .............. 1
n. WHOPPING COUGH .............. 1
o. POLIO ....................... 1
p. DIABETES MELLITUS ............ 1
q. CYSTIC FIBROSIS ............... 1
r. DEVELOPMENTAL DISABILITIES 1
s. MUSCULAR DYSTROPHY .......... 1
1. CEREBRAL PALSY ............... 1
u. ATTENTION DEFICIT ............. 1
v. LEARNING DISABILITY ........... 1
w. NONE OF THE ABOVE ........... 1

Q8. Does [ I have any allergies?

1 .................. YES
2 .................... NO [GOTO Q9]

 

Please specify anything [ I is allergic to (including
pollen, drugs, food, hay fever, sinus trouble, animals, etc.)

a. b.

 

 

c. d.

 

 

 

 

 

Q9. Has [ I had recurrent ear infections?

1 .................. YES
2 ................... NO [GOTO Q 10]

 

AGE STARTED: , to AGE OF RECURRENCE: ,

(year, month) . (year, month)

 

 

 

98

Q9a. Was ear surgery required?

1 .................. YES
2 ................... NO [GOTO Q10]

 

O
‘ 9

(var. momh) . I

- AGE WHEN EAR SURGERYOCCURRED

 

 

 

Q10. How many times (instances) has [ I been sick with common illnesses in the last 12
months? (colds, flu, sore throats, etc.) Please check the number below that best approximates
how many times [ I has been sick with common illnesses.

(Circle One)

a NEVER ....................... o
b 1 DAY ........................ 1
c. 2 DAYS ....................... 2
d. 35 DAYS ...................... 3
e. 6-10 DAYS ..................... 4
f. 11-20 DAYS .................... 5
g. 2160 DAYS .................... 6

Q11. Has [ I had any uncommon childhood illnesses?

1 ................. YES
2 .................. NO [GOTO Q12]

 

ILLNESSES

a. b. ‘ ’ c.

 

 

 

 

 

Q12. Has [ I received any of the following immunizations? (Circle all that apply)

DPT 1 ........ 1 POLIO 1 ........... l MUMPS ................

DPT 2 ........ l POLIO 2 ........... 1 RUBELLA ..............

DPT 3 ........ 1 POLIO BOOSTER 1 . . . . l COMBINATION

DPT BOOSTER 1 l POLIO BOOSTER 2 . . . . 1 MEASLES/MUMPS/RUBELLA .

DPT BOOSTER 2 1 MEASLES .......... 1 HIB ..................
OTHER ................
Specify

 

Q13. If your child had any serious reactions to any of the immunizations list the appropriate ones.

1 2 3 4 5 6

 

 

99

V. SLEEP BEHAVIOR

Ql. Please describe I I’s sleep behavior in the last year:

a. Usually asleep by P.M.
b. Usually awake by A.M.

Q2. For each item, circle the number that best describes [ I.

NEVER SOMETIME OFTEN VERY OFTEN

a. EASILY FATIGUED ............... O 1 2 3
b. SLEEP UNUSUALLY SOUNDLY ...... O l 2 3
c. TROUBLE GETTING TO SLEEP ...... 0 1 2 3
d. HAS TO SLEEP IN PARENTAL BED . . . 0 1 2 3
e. RESTLESS, TOSSES A LOT ......... 0 1 2 3
f. FALLS OUT OF BED .............. O 1 2 3
g. SWEATS IN SLEEP ............... 0 l 2 3
h. TALKS, LAUGHS OR CRIES IN SLEEP . 0 1 2 3
i. GRINDS TEETH IN SLEEP .......... 0 1 2 3
j. SNORES ....................... 0 l 2 3
k. SLEEPWALKS OR WANDERS AT NIGHT O 1 2 3
l. PECULIAR POSITIONS IN SLEEP ..... 0 1 2 3
m. NIGHTMARES .................. O 1 2 3
11. NIGHT TERRORS ................ O 1 2 3

(CHILD HAS BAD DREAMS BUT CANNOT
WAKE UP TO 17511. WHAT IS THE MATIER,
DOES NOT REMEMBER IN THE MORNING)
VI. TOILETING
Q1. At what age was [ I completely toilet trained?

a. For urination:

 

DAY: , NIGHT ,

(year, month) (year, month)

 

 

 

 

b. For bowels:

 

DAY: , NIGHT ,

(year, month) (year, month)

 

 

 

 

100

Q2. Has [ I experienced bed wetting or day time wetting accidents since toilet
training was completed?

1 ................ YES [GOTO Q2a]
2 ................. NO [GOTO Q3]

Q2a. What type of accidents?

(Circle One)

Day time wetting .......... 1
Bed wetting .............. 2
Both .................. 3

Q2b. What age did these accidents Start?

 

9

 

 

 

 

year, month

Q2e. How often?

(Circle One)

Every night ................ 1

1 or 2 times a week .......... 2

1 or 2 times a month .......... 3

Less than once a month,

but at least once a year ........ 4

Q2d. Does [ I still have accidents?

1 ................ YES [GOTO Q3]
2 ................... NO [GOTO Q2e]

Q2e. Age controlled?

 

9

year, month

 

 

 

Q3. Has [ I experienced soiling accidents since he completed toileting training?

1 ................ YES [GOTO Q3a]
2 ................. NO [GOTO VII, Q1]

101

 

 

 

 

 

 

 

 

 

 

Q3a. What type of accidents?

(Circle One)

Day time soiling ............. 1

Night time soiling ............ 2

Both .................... 3
Q3b. What age did these accidents start?

year: month

Q3c. How often?

(Circle One)

Every night ................ 1

1 or 2 times a week .......... 2

1 or 2 times a month .......... 3

Less than once a month,

but at least once a year ........ 4
Q3d. Does [ I still have accidents?

1 ................ YES [GOTO VII, Q1]
2 ................. NO [GOTO Q3e]
Q3e. Age controlled?
yea; month. 1

VII. HEARING
Q1. Has [ I hearing ever been evaluated?

 

1 ................ YES
2 ................. NO [GOTO Q2]
' . a. What age?
b. By Whom? '9

 

. (Audiologist, family dOctor, other)

e. Results?

 

(Normal, some hearing lass. etc.)

 

 

 

Q2. Have you ever wondered if [ I can hear properly?
1 ................... YES
2 ................... NO
Q3. Does [ I have difficulty understanding or remembering instructions?
1 ................... YES
2 ................... NO
Q4. Is [ I’s hearing too Sharp, or hears every little thing?
1 ................... YES
2 ................... NO
Q5. Is [ I easily irritated by noise?
1 ................... YES
2 ................... NO
VIII. VISION
Q1. Has [ I’s vision ever been checked?
1 ................ YES
2 ................. NO [GOTO, Q2]
2a. When? . , ’ (Month, year) ’
'br.ByWholm?b * _ ' 4 ‘ ,
' (Ophthalmologist [MD], Optometrist [0.0. I) V
c. Results? _ I ‘ ' I ' -
' ' , (Normal, near sighted, far sighted, etc.)
Q2. Does [ I wear glasses or contact lenses?

102

 

 

 

 

 

 

 

1 ................... YES
2 .................... NO [GOTO Q3]

Q4.

Q5.

IX.

Q1.

Q2.

Q3.

103
Q3. Do [ I’s eyes deviate (turn inward, upward, etc.)?

1 .................... YES
2 .................... N O [GOTO Q4]

 

 

 

V i (Please Describe) ' ‘ . :

 

 

Are there any other symptoms of eye problems (red eyes, excessive rubbing, inflamed,
etc. )?

1 .................... YES
2 .................... N O [GOTO Q5]

 

 

 

. (Pleage Describe) I

 

 

Do any other aspects [ I’s visual behavior concern you?

1 .................... YES
2 .................... NO [GOTO IX]

 

 

 

. Qleage Describel .

 

 

DENTAL HEALTH

Does [ I take fluoride daily?

 

 

1 ................... YES
2 .................... NO
Has [ I been to the dentist?
1 ................. YES
2 ................... NO
Age at, last visit: '1 ,1 g
' Year. month

 

 

 

LIST OF REFERENCES

LIST OF REFERENCES

 

 

 

_agg revised child behavior profile. Burlington, VT: University Associates in
Psychiatry.

 

Alterman, A. I., Bridges, K. R., & Tarter, R. E. (1986). Drinking behavior of
high-risk college men: Contradictory preliminary findings. Alcoholism:
Clinical an_d Experimental Research, m, 1-6.

Alterman, A. I., Searles, J. S., & Hall, J. G. (1989). Failure to find differences in
drinking behavior as a function of familial risk for alcoholism: A replication.
Journal o_f Abnormal Psychology, _9§, 50-53.

American Psychiatric Association. (1980). Diagnostic amt] Statistical Manual, (3rd
Ed.). Washington DC: Author.

 

American Psychiatric Association. (1987). Diagnostic m Statistical Manual, (3rd
Ed.-Revised). Washington DC: Author.

 

American Psychiatric Association. (1994). Diagnostic and Statistical Manual, (4th
Ed.). Washington DC: Author.

 

Anderson, E., & Quast, W. (1983). Young children in alcoholic families: A mental
health needs-assessment and an intervention/prevention strategy. Journal o_f
Primag Prevention, 3, 174-187.

Aronson, H. , & Gilbert, A. (1963). Preadolescent sons of male alcoholics: An
experimental study of personality patterning. Archives 9_f General Psychiatgy,
3S, 235-241.

 

Aronson, M., Kyllerman, M., Sabel, K. G., Sandin, B., & Olegard, R. (1985).
Children of alcoholic mothers: Developmental, perceptual, and behavioral

characteristics as compared to matched controls. Acta Paediatrica
Scandinavia, 14, 27-35.

104

105

Babor, T. F., Hoffrnann, M., DelBoca, F. K., Hesselbrock, V., Meyer, R. E.,
Dolinsky, Z. S., & Rounsaville, B. (1992). Types of alcoholics: 1. Evidence
for an empirically derived typology based on indicators of vulnerability and
severity. Archives o_f General Psychiatg, 53, 599-608.

Babor, T. F ., & Lauerman, R. J. (1986). Classification and forms of inebriety:
Historical antecedents of alcohol typologies. In M. Galanter (Ed.), Recent
developments 1p alcoholism (Vol. 4, pp. 113-144). New York: Plenum Press.

Babor, T. F., & Meyer, R. E. (1986). Overview: Typologies of alcoholics. In M.
Galanter, (Ed.), Recent developments ip alcoholism (Vol. 4. pp 105-111).
New York: Plenum Press.

Bell, B., & Cohen, R. (1981). The Bristol Social Adjustment Guide: Comparison
between the offspring of alcoholic and non-alcoholic mothers. British Journal
pf Clinical Psychology, E, 93-95.

 

 

Bennett, L. A., Wolin, S. 1., & Reiss, D. (1988). Cognitive, behavioral, and
emotional problems among school-age children of alcoholic parents.

A American Journal pf Psychiatry, £5, 185-190.

Berkowitz, A., & Perkins, H. W. (1988). Personality characteristics of children of
alcoholics. Journal o_f Consulting M Clinical Psychology, 16, 206-209.

 

Biek, J. (1981). Screening test for identifying adolescents adversely affected by a

 

Bingham, C. R., & Crockett, L. J. (in press). Longitudinal adjustment patterns of
boys and girls experiencing early, middle, and late sexual intercourse.

Developmental Psychology.

Bingham, C. R., Fitzgerald, B., Fitzgerald, H. E., & Zucker, R. A. (1996, June).
Prenatal Histog, Parental Alcoholism, an_d E Development pf Preschool-
Agg Sons of Alcoholics. Poster session to be presented at the annual
meeting of the Research Society on Alcoholism, Washington, DC.

 

 

Bingham, C. R., Zucker, R. A., & Fitzgerald, H. E. (1996). M Laid Variation
m Problem Behavior Development across @ Preschool m E_aply School
Years among m o_f Alcoholics. Unpublished manuscript, Michigan State
University, East Lansing, MI.

 

Bohman, M., Sigvardsson, S., & Cloninger, C. (1981). Maternal inheritance of
alcohol abuse: Cross-fostering analysis of adopted women. Archives of
General Psychiatpy, _3_8_, 965-969.

106

Brook, J. S., Whiteman, M., Gordon, A. S., & Cohen, P. (1986a). Dynamics of
childhood and adolescent personality traits and adolescent drug use.

Developmental Psychology, 2_2_, 403-414.

Brook, J. S., Whiteman, M., Gordon, A. S., & Cohen, P. (1986b). Some models
and mechanisms for explaining the impact of maternal and adolescent
characteristics on adolescent stage of drug use. Developmental Psychology,
2_2, 460-467.

Brook, J. S., Whiteman, M., Gordon, A. S., & Cohen, P. (1989). Changes in drug
involvement: A longitudinal study of childhood and adolescent determinants.

Psychological Reports, _6__5_, 707-726.

Brown, J ., Babor, T. F., Litt, M. D., & Kranzler, H. R. (1994). The Type A/
Type B distinction: Subtyping alcoholics according to the indicators of
vulnerability and severity. In T. F. Babor, V. Hesselbrock, R. E., Meyer, &
W. Shoemaker (Eds.), Types o_f alcoholics: Evidence fr_o_m_ clinical,
experimental, app genetic research (pp. 23-33). New York: The New York
Academy of Sciences.

 

Cantwell, D. P. (1972). Psychiatric illness in the families of hyperactive children.
Archives of General Psychiag, _2_7, 414-417.

Chafetz, M., Blane, H., & Hill, M. (1971). Children of alcoholics. marterly

Chassin, L., Rogosch, F., & Barrera, M. (1991). Substance use and
symptomatology among adolescent children of alcoholics. Journal 91“
Abnormal Psychology, 100, 449-463.

Churchill, J. C., Broida, J. P., & Nicholson, N. (1990). Locus of control and self-

373-376.

Cloninger, C. R., Bohman, M., & Sigvardsson, S. (1981). Inheritance of alcohol
abuse. Archives o_f General Psychiam, fl, 861-868.

 

Conrad, M., & Hammen, C. (1989). Role of maternal depression in perceptions of
child maladjustment. Journal of Consulting m Clinical Psychology, Q, 663-
667.

 

Cotton, N. (1979). The familial incidence of alcoholism: A review. Journal pf
Studies g1 Alcohol, fl, 89-116.

107

Drejer, K., Theilgaard, A., Teasdale, T. W., Schulsinger, F., & Goodwin, W.
(1985). A prospective study of young men at high risk for alcoholism:
Neuropsychological assessment. Alcoholism: Clinical gn_d Experimental
Research, 2, 498-502.

Earls, F. J. (1987). On the familial transmission of child psychiatric disorder.
Journal o_f Child Psychology, Psychiam, M Allied Disciplines, 28, 791-802.

>1—Guebaly, N., & Offord, D. R., (1977). The offspring of alcoholics: A critical
review. American Journal o_f Psychiatry, 134, 357—365.

Ellis, D. A. (1992). Typological differences ip patterns o_f fig among young
children o_f alcoholics. Unpublished Dissertation, Michigan State University.

Ellis, D. A., Bingham, C. R., Zucker, R. A., & Fitzgerald, H. E. (1996).

Young Alcoholic Families. Manuscript submitted for publication.

Ervin, C., Little, R., Streissguth, A., & Beck, D. (1984). Alcoholic fathering and
its relation to child’s intellectual development: A pilot investigation.
Alcoholism: Clinical an_d Experimental Research, 8, 362-365.

Feighner, J., Robins, E., Guze, S., Woodruff, R., Winokur, G., & Munoz, R.
(1972). Diagnostic criteria for use in psychiatric research. Archives o_f
General Psychiatgg, 26, 57-63.

Fine, E., Yudin, L., Holmes, J., & Heinemann, S. (1976). Behavioral disorders in
children with parental alcoholism. Annals o_f E New York Academy o_f
Science, _2_73, 507-517.

Finn, P. R., & Pihl, R. O. (1987). Men at high risk for alcoholism: The effect of
alcohol on cardiovascular response to unavoidable shock. Journal o_f
Abnormal Psychology, 9_6_, 230-236.

Finn, P. R., & Pihl, R. O. (1988). Risk for alcoholism: A comparison between two
different groups of sons of alcoholics on cardiovascular reactivity and
sensitivity to alcohol. Alcoholism: Clinicgl app Experimental Research, 1_2_,
742-747.

Fitzgerald, H. E., Jones, M. A., Maguin, E., Zucker, R. A., & Noll, R. B. (1991).
Assessing papenta] antisocial behavior i_n alcoholic gig nonalcoholic families.
Unpublished manuscript, Michigan State University, East Lansing, MI.

108

Fitzgerald, H. E., Sullivan, L. A., Ham, H. P., Zucker, R. A., Bruckel, S.,
Schneider, A. M., & Noll, R. B. (1993). Predictors of behavior problems in
three-year-old sons of alcoholics: Early evidence for the onset of risk. C_hilc_1
Development, 84, 110-123.

Gabrielli, W., & Mednick, S. (1983). Intellectual performance in children of

Glenn, S. W., & Nixon, S. J. (1991). Application of Cloninger’s subtypes in a
female alcoholic sample. Alcoholism: Clinical m Exxrimental Research,
18, 851-857.

Gomberg, E. S. L., & N irenberg, T. D. (1993). Antecedents and consequences. In
E. S. L. Gomberg & T. D. Nirenberg (Eds.), Women gpd substance abuse
(pp. 118-141). New Jersey: Ablex Publishing.

Goodwin, D. W., Schulsinger, F ., Herrnansen, L., Guze, S. B., & Winokur, G.
(1975). Alcoholism and the hyperactive child syndrome. Journal o_f Nervous
m Mental Disea_s_e, @, 349-353.

Grant, B. F., Harford, T. C., Dawson, D. A., Chou, P., Dufour, M., & Pickering,
R. (1994). Prevalence of DSM-IV alcohol abuse and dependence: United

 

Harter, S. (1982). The Perceived Competence Scale for Children. Child
Development, 83;, 87-97.

Ham, H. P., Fitzgerald, H. E., & Zucker, R. A. (1993, June). Recent evidenpp pf
behavioral dysregplation in sons of male alcoholics. Paper presented at

Research Society on Alcoholism Scientific Conference, San Antonio, TX.

Hegedus, A. M., Alterman, A. I., & Tarter, R. E. (1984). Learning achievement in
sons of alcoholics. Alcoholism: Clinical 2_11_1(_1 Experimental Research, 8, 330-
333.

Helzer, J. E. (1987). Epidemiology of alcoholism. Journal 91‘ Consulting and
Clinical Psychology, 88, 284-292.

Herjanic, B., Herjanic, M., Penick, E., Tomelleri, C., & Armbruster, R. (1977).
Children of alcoholics. In F. A. Seixas (Ed.), Currents ip alcoholism (Vol.
2, pp. 445-455). New York: Grune & Stratton.

Herjanic, B., Herjanic, M., Wetzel, R., & Tomelleri, C. (1978). Substance abuse:
Its effect on offspring. Research Communications i_I_1 Psychology, Psychiatg
a_ng Behavior, 8, 65-75.

109

Hesselbrock, M. N. (1986). Alcohol typologies: A review of empirical evaluations
of common classification schemes. In M. Galanter (Ed.), Recent
developments iii alcoholism (Vol. 4, pp. 191-206). New York: Plenum Press.

Hesselbrock, M. N., & Hesselbrock, V. M. (1993). Depression and antisocial
personality disorder in alcoholism: Gender comparison. In E. S. L. Gomberg
& T. D. Nirenberg (Eds.), Women M substance abuse (pp. 142-161). New
Jersey: Ablex Publishing.

 

Hesselbrock, M. N., Hesselbrock, V. M., Babor, T. F., Stabenau, J. R., Meyer, R.
E., & Weidenman, M. (1984). Antisocial behavior, psychopathology and
problem drinking in the natural history of alcoholism. In D. W. Goodwin, K.
T. Van Dusen, & S. A. Mednick (Eds.), Longitudinal research ip alcoholism
(pp. 197-214). Boston: Kluwer-Nijhoff Publishing.

 

Hesselbrock, V., Bauer, L. 0., Hesselbrock, M. N., & Gillen, R. (1991).
Neuropsychological factors in individuals at high risk for alcoholism. In M.
Galanter (Ed.), Recent developments ip alcoholism (Vol. 9, pp. 21-40). New
York: Plenum Press.

 

Hill, S. Y. (1993). Genetic vulnerability to alcoholism in women. In E. S. L.
Gomberg & T. D. Nirenberg (Eds.), Women m substance abuse (pp. 42-
61). New Jersey: Ablex Publishing.

Hinshaw, S. (1987). On the distinction between attentional deficits/hyperactivity and
conduct problems/aggression in child psychopathology. Psychological
Bulletin, M_, 443-463.

Hughes, J. M. (1977). Adolescent children of alcoholic parents and the relationship
of Alateen to these children. Journal pf Consulting fl Clinical Psychology,
4_5, 946-947.

 

Jacob, T ., & Leonard, K. (1986). Psychosocial functioning in children of alcoholic

 

41, 373-380.

Jastak, S., & Wilkinson, G. S. (1984). m Wide Range Achievement Igs_t -
revised: Administration manual. Wilmington, DE: Jastak Associates.

 

 

Jellinek, E., M. (1960). _T_h_e disease concept o_f alcoholism. New Haven, CT:
Hillhouse Press.

 

Johnson, J. L., & Rolf, J. E. (1988). Cognitive functioning in children from
alcoholic and non-alcoholic families. British Journal o_f Addiction, 88, 849-
857.

110

Jones, M. C. (1968). Personality correlates and antecedents of drinking patterns in
adult males. Journal 9f Consulting m Clinical Psychology, Q, 2-12.

Joreskog, K. G., & Sorbom, D. (1993). LISREL 881; User’s Refererg Guide.
Chicago: Scientific Software International.

Kern, J., Hassett, C., Collipp, P., Bridges, C., Solomon, M., & Condren, R.
(1981). Children of alcoholics: Locus of control, mental age, and zinc level.
Journal o_f Psychiatric Treatment M Evaluation, 8, 169-173.

Knop, J., Teasdale, T. W., Schulsinger, F., & Goodwin, D. W. (1985). A
prospective study of young men at high risk for alcoholism: School behavior

Knowles, E., & Shroeder, D. A. (1989). Familial and personality correlates of
alcohol-related problems. Addictive Behaviors, 1_4, 537-543.

Lahey, B. B., & Loeber, R. (1994). Framework for a developmental model of
oppositional defiant disorder and conduct disorder. In D. K. Routh (Ed.),
Disruptive behavior disorders ip childhood (pp. 139-180). New York:
Plenum Press.

Lex, B. W., Sholar, J. W., Bower, T., & Mendelson, J. H. (1991). Putative type II
alcoholism characteristics in female third DUI offenders in Massachusetts: A
pilot study. Alcohol, 8, 283-287.

 

Litt, M. D., Babor, T. F., DelBoca, F. K., Kadden, R. M., & Cooney, N. L.
(1992). Types of alcoholics, 11: Application of an empirically derived
typology to treatment matching. Archives 91’ General Psychiatgy, 49, 609-
614.

 

Loper, R. G., Kammeier, M. L., & Hoffmann, H. (1973). MMPI characteristics of
college freshmen who later became alcoholics. Journal 91" Abnormal
Psychology, 8;, 159-162.

 

Lund, C., & Landesman-Dwyer, S. (1979). Pre-delinquent and disturbed
adolescents: The role of parental alcoholism. In M. Galanter (Ed.), Currents
ip alcoholism (Vol. 5, pp. 338-348). New York: Grune & Stratton.

MacAndrew, C. (1965). The differentiation of male alcoholic outpatients from
nonalcoholic psychiatric outpatients by means of the MMPI. Quarterly

Mann, L. M., Chassin, L., & Sher, K. J. (1987). Alcohol expectancies and the risk
for alcoholism. Journal pf Consulting m Clinical Psychology, _5_5, 411-417.

111

Marcus, A. M. (1986). Academic achievement in elementary school children of
alcoholic mothers. Journal o_f Clinical Psychology, 4_2, 372-376.

McCord, W., & McCord, J. (1960). O_rigi_n_s 01mm. Stanford, CA: Stanford
University Press.

McKenna, T., & Pickens, R. (1983). Personality characteristics of alcoholic

Merikangas, K. R., Weissman, M. M., Prusoff, B. A., Pauls, D. L., & Leckman, J.
F. (1985). Depressives with secondary alcoholism: Psychiatric disorders in

 

Moos, R. H., & Billings, A. G. (1982). Children of alcoholics during the recovery
process: Alcoholic and matched control families. Addictive Behaviors, 1,
155-163.

Morrison, J. R., & Stewart, M. A. (1971). A family study of the hyperactive child
syndrome. Biological Psychiat_ry, 8, 189-195.

Mueller, C. W., & Parcel, T. L. (1981). Measures of socioeconomic status:
Alternatives and recommendations. Child Development, 2,, 13-30.

Murphy, R. T., O’Farrell, T. J., Floyd, F. J., & Connors, G. J. (1991). School
adjustment of children of alcoholic fathers: Comparison to normal controls.
Addictive Behaviors, 1_6, 275-287.

Noll, R. B., & Zucker, R. A. (1980). _T_hp structure o_f antisocial behavior i_n
different populations. Unpublished manuscript, Michigan State University,
East Lansing, MI.

Noll, R. B., Zucker, R. A., Fitzgerald, H. E., & Curtis, W. J. (1992). Cognitive
and motoric functioning of sons of alcoholic fathers and controls: The early
childhood years. Developmental Psychology, 28, 665-675.

Offord, D., Allen, N., & Abrams, N. (1978). Parental psychiatric illness, broken
bones, and delinquency. Journal o_f E American Academy pf Child
Psychiatg, 11, 224-238.

Pihl, R. 0., Peterson, J ., & Finn, P. (1990). Inherited predisposition to alcoholism:
Characteristics of sons of male alcoholics. Journal pf Abnormal Psychology,
3, 291-301.

112
Prewett, M., Spence, R., & Chaknis, M. (1981). Attribution of causality by

370.

Richters, J., & Pellegrini, D. (1989). Depressed mother’s judgements about their
children: An examination of the depression-distortion hypothesis. Child
Development, 60, 1068-1075.

Rimmer, J. (1982). The children of alcoholics: An exploratory study. Children ind
Youth Services Review, 4, 365-373.

 

 

 

Roberts, K., & Brent, E. (1982). Physician utilization and illness patterns in

Robins, L. N. (1986). The consequences of conduct disorder in girls. In D.
Olweus, J. Block, & M. Radke-Yarrow (Eds.), Development o_f antisocial a_n_d_
prosocial behavior (pp. 385-414). New York: Academic Press.

 

Robins, L., Helzer, J., Croughan, J ., & Ratcliff, K. S. (1980). m NIMH
Diagpostic Interview Schedule: 13 history, characteristics ad validig. St.
Louis, MO: Washington University School of Medicine.

Robins, L., West, P., Ratcliff, K., & Herjanic, B. (1978). Father’s alcoholism and
children’s outcomes. In F. A. Seixas (Ed.), Currents ip alcoholism (Vol. 4,
pp. 313-327). New York: Grune & Stratton.

Rolf, J. E., Johnson, J. L., Israel, E., Baldwin, J., & Chandra, A. (1988).
Depressive affect in school-aged children of alcoholics. British Journal pf
Addiction, 88, 841-848.

Roosa, M. W., Sandler, I. N., Beals, J., & Short, J. L. (1988). Risk status of
adolescent children of problem drinking parents. American Journal o_f

Community Psychology, _1__6_, 225-239.

Rubio—Stipec, M., Bird, H., Canino, G., Bravo, M., & Alegria, M. (1991).
Children of alcoholic parents in the community. Journal o_f Studies pp
Alcohol, 82, 78-88.

o_f m literature. New York: Children of Alcoholics Foundation.

 

Rydelius, P. (1983). Alcohol-using teenage boys. Acta Psychiatrica Scandinavia,
68, 368-380.

113

Sattler, J. M. (1982). Assessment of Children’s Intelligence 1118 Smcial Abilities
(2nd Edition). Boston: Allyn & Bacon, Inc.

Saunders, G. R., & Schuckit, M. A. (1981). MMPI scores in young men with

1_62, 456-458.

Schuckit, M. A. (1982). Anxiety and assertiveness in sons of alcoholics and control.
Journal pf Clinical Psychiatg, fl, 238-239.

Schuckit, M. A., & Chiles, J. (1978). Family history as a diagnostic aid in two

176.

Schulsinger, F., Knop, J ., Goodwin, D. W., Teasdale, T. W., & Mikkelson, U.
(1986). A prospective study of young men at high risk for alcoholism: Social
and psychological characteristics. Archives o_f General Psychiatg, 28, 755-
760.

Searles, J. S., & Windle, M. (1990). Introduction and Overview: Salient issues in
the children of alcoholics literature. In M. Windle & J. S. Searles (Eds.),
Children o_f Alcoholics: Critical Perspectives. New York: The Guilford Press

(pp- 1-8).

Seilhamer, R. A., & Jacob, T. (1990). Family factors and adjustment of children of
alcoholics. In M. Windle & J. S. Searles (Eds.), Children pf alcoholics:
Critical p_ersmtives (pp. 168-186). New York: Guilford Press.

 

 

 

Selzer, M. L., Vinokur, A., & Van Rooijen, L. (1975). A self-administered short

 

 

research. Chicago: The Univ of Chicago Press.

Sher, K. J., Walitzer, K. S., Wood, P. K., & Brent, E. E. (1991). Characteristics
of children of alcoholics: Putative risk factors, substance use and abuse, and
psychopathology. Journal o_f Abnormal Psychology, 10_0, 427—448.

Steinhausen, H., Gobel, D., & Nestler, V. (1984). Psychopathology in the offspring
of alcoholic parents. Journal o_f t_h§ American Academy o_f Child Psychiat_ry,
E. 465-471.

 

114

Steinhausen, H., Nestler, V., & Huth, H. (1982). Psychopathology and mental
functions in the offspring of alcoholic and epileptic mothers. Journal o_f 81;
American Academy o_f Child Psychiap'y, 2_1, 268-273.

Stevens, 6., & Featherman, D. L. (1981). A revised socioeconomic index of
occupational status. Social Science Research, m, 364-395.

 

Stewart, M., deBlois, S., & Cummings, C. (1980). Psychiatric disorder in the
parents of hyperactive boys and those with conduct disorder. Journal o_f Child

Psychology, Psychiag, m Allied Disciplines, 22, 283-292.

Stewart, M., deBlois, S., & Singer, S. (1979). Alcoholism and hyperactivity
revisited: A preliminary report. In M. Galanter (Ed.), Currents ip alcoholism
(Vol. 5, pp. 349-357).

 

Streissguth, A. P. (1976). Psychologic handicaps in children with the fetal alcohol
syndrome. Annals of the New York Academy o_f Sciences, 23, 140-145.

 

 

Streissguth, A. P., Little, R. E., Herman, C., & Woodell, S. (1979). IQ in children
of recovered alcoholic mothers compared to matched controls. Alcoholism:
Clinical g4 Experimental Research, 8, 197.

Tarter, R., Hegedus, A., Goldstein, G., Shelly, C., & Alterman, A. (1984).
Adolescent sons of alcoholics: Neuropsychological and personality
characteristics. Alcoholism: Clinical m Expprimental Research, 8, 216-222.

Tarter, R. E., Jacob, T., & Bremer, D. A. (1989). Cognitive status of sons of
alcoholic men. Alcoholism: Clinical an_d Exmrimental Research, 18, 232-
235.

Terrnan, L. M., & Merrill, M. A. (1973). Stanford-Binet Intelligence Scale: Manual
1Q! Lh_e third revision (Form L-M). Boston: Houghton Mifflin CO.

US. Department of Health and Human Services (1993). Eighth Smcial Report LO
E US Congress pp Alcohol apg Health. Washington, DC: Author.

 

Vaillant, G. (1983). m natural histogg pf alcoholism. Cambridge, MA: Harvard
University Press.

Wechsler, D. (1974). Wechsler Intelligence Scale m Children - revised. New
York: The Psychological Corporation.

Werner, E., E. (1986). Resilient offspring of alcoholics: A longitudinal study from

 

b"

115

West, M. O., & Prinz, R. J. (1987). Parental alcoholism and childhood
psychopathology. Psychological Bulletin, 1_0_2, 204-218.

Wilsnack, S. C., & Wilsnack, R. W. (1993). Epidemiological research on women’s
drinking: Recent progress and directions for the 19903. In E. S. L. Gomberg
& T. D. Nirenberg (Eds.), Women a_nd substance m (pp. 62-99). New
Jersey: Ablex Publishing.

 

Wilson, J. R., & Nagoshi, C. T. (1988). Adult children of alcoholics: Cognitive and
psychomotor characteristics. British Journal _o_f Addiction, 8_3, 809-820.

Windle, M. (1990). Temperament and personality attributes of children of
alcoholics. In M. Windle & I. S. Searles (Eds.), Children o_f alcoholics:
Critical pprspectives (pp. 129-167). New York: The Guilford Press.

 

Windle, M., & Searles, J. S. (1990). Children o_f alcoholics: Critical pprspgctives.
New York: The Guilford Press.

 

 

Zucker, R. A. (1987). The four alcoholisms: A developmental account of the
etiologic process. In P. C. Rivers (Ed.), Nebraska symposium pp motivation:
Alcohol m addictive behavior (Volume 34, pp.27-83). Lincoln: Univ. of
Nebraska Press.

 

 

Zucker, R. A. (1994). Pathways to alcohol problems and alcoholism: A
developmental account of the evidence for multiple alcoholisms and for
contextual contributions to risk. In R. A. Zucker, J . Howard, & Boyd, G.
M. (Eds.), fl; development p_f alcohol problems: Exploring ;h_e
biopsychosocial matrix o_f {i_sk (Research Monograph No. 26, pp. 225-289).
Rockville, MD: National Institute on Alcohol Abuse and Alcoholism.

 

Zucker, R. A., & Barron, F. H. (1973). Parental behaviors associated with problem
drinking and antisocial behavior among adolescent males. In M. E. Chafetz
(Ed.), Research g alcoholism: I. Clinical problems a_nd_ sgcial populations
(DHEW Publication No. 74-675, pp. 276-296). Washington, DC:
Government Printing Office. '

 

Zucker, R. A., Ellis, D. A., Bingham, C. R., & Fitzgerald, H. E. (in press). The
development of alcoholic sybtypes: Risk variation among alcoholic families
during the early childhood years. Alcohol, Health, a_ng Research World.

116

Zucker, R. A., Ellis, D. A., & Fitzgerald, H. E. (1994a). Developmental evidence
for at least two alcoholisms: I. Biopsychosocial variation among pathways into
symptomatic difficulty. In T. F. Babor, V. Hesselbrock, R. E. Meyer, & W.
Shoemaker (Eds.), Types o_f alcoholics: Evidence m clinical, experimental,
a_nd_ genetic research (pp. 134-146). New York: The New York Academy of
Sciences.

 

Zucker, R. A., Ellis, D. A., & Fitzgerald, H. E. (1994b). Other evidence fo_r a_t
least tw_o alcoholisms: 11. IE eaee m lifetime antisocialig a_s e basis pf
differentiation. Manuscript submitted for publication.

 

 

Zucker, R. A., Ellis, D. A., Fitzgerald, H. E., Bingham, C. R., & Sanford, K. P.
(in press). Other evidence for at least two alcoholisms 11: Life course
variation in antisociality and heterogeneity of alcoholic outcome.

Development m Psychopathology.

Zucker, R. A. , & Fillmore, K. M. (1968, September). Motivational factors and
problem drinking among adolescents. Paper presented at the 28th
International Congress on Alcohol and Alcoholism. Washington DC.

Zucker, R. A., & Fitzgerald, H. E. (1992a). Risk egg coping ip children 91
alcoholics (NIAAA grant ROI AA-07065). Unpublished manuscript,
Michigan State University, East Lansing, MI.

Zucker, R. A., & Fitzgerald, H. E. (1992b). Child Health M Development
Histog. Unpublished instrument, Michigan State University, E. Lansing, MI.

Zucker, R. A., Fitzgerald, H. E., & Moses, H. D. (1995). Emergence of alcohol
problems and the several alcoholisms: A developmental perspective on
etiologic theory and life course trajectory. In D. Cicchetti & D. J. Cohen

(Eds.), Developmental Psychopathology: Risk, Disorder, em Adaptation
(Vol. 2, pp. 677-711). New York: Wiley.

Zucker, R. A., Fitzgerald, H. E., & Noll, R. B. (1990). Drinkng 8118 drug history
(rev. ed., version 4). Unpublished instrument, Michigan State University,
East Lansing, MI.

Zucker, R. A., & Gomberg, E. S. L. (1993). Alcoholism _aLd antisocial comorbidig

for publication.

Zucker, R. A., & Noll, R. B. (1980). m antisocial behavior checklist.
Unpublished instrument, Michigan State University, East Lansing, MI.

 

117

Zucker, R. A., Noll, R. B., & Fitzgerald, H. E. (1986). Risk a_n_(_1 coping 1p
children o_f alcoholics (NIAAA grant AA-07065). Unpublished manuscript,
Michigan State University, East Lansing, MI.

Zucker, R. A., Noll, R. B., Ham, H. P., Fitzgerald, H. E., & Sullivan, L. S.

Reliabiligr aLd Validity Studies. Unpublished manuscript, Michigan State
University, East Lansing, MI.

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